INESCTEC.OCEAN invites researchers with a PhD and professionals of recognised scientific and/or professional merit to submit an expression of interest for the position of Chair Holder in Condition and Structural Health Monitoring of Floating Offshore Wind Platforms.

The Chair aims to strengthen research and innovation in floating offshore wind, fostering the connection between academic excellence, applied research, and industry’s technological challenges.

🔹 Host Institutions and Partnerships

• Employing Institution: FEUP – Faculty of Engineering of the University of Porto
• Research Host and Operational Coordination: INESC TEC (INESCTEC.OCEAN)
• Industrial Partner: Ocean Winds
• Co-funding: FCT and Ocean Winds

🔹 Areas of Expertise

• Condition & Structural Health Monitoring (CSHM)
• Structural integrity and offshore structures
• Digital Twin and predictive maintenance
• Integration of sensing, instrumentation, and data analysis
• Hydrodynamics, numerical modelling, structural analysis
• Reliability and critical engineering systems
• Asset Integrity Management

🔹 Profile

We are looking for a PhD researcher with international recognition and a consolidated track record in areas relevant to the Chair, including experience in research and innovation, team leadership, supervision of researchers and students, teaching, and collaboration with academic institutions and relevant industrial partners.

The position will be developed in articulation with a renowned Higher Education Institution (FEUP) and with INESC TEC, where the Chair Holder will be an integrated researcher at INESC TEC, also benefiting from a connection to an industrial partner in the offshore wind sector (Ocean Winds).

📍 Location: Porto
⏱️ Commitment: Full-time (35 hours/week)
📅 Initial duration: 1 year, renewable up to a maximum of 4 years
🎓 Academic Position: Invited Associate Professor or Invited Full Professor, according to the candidate’s profile and seniority.

🔹 Expression of Interest

Interested candidates should submit:

• Updated CV
• Letter of expression of interest
• Brief description of scientific, technological, and/or industrial background
• Information on leadership experience, supervision, and collaboration with industry

📩 Applications should be addressed to: inesctecocean@inesctec.pt
📅 Deadline: 28 October, 2026
📌 Subject: Expression of Interest – Chair in Condition and Structural Health Monitoring of Floating Wind Energy Platforms

ℹ️ This expression of interest constitutes a step in identifying potential candidates and does not replace the eventual formal recruitment procedure.

🌟 Why join this Chair?

This Chair offers a unique opportunity to lead innovation in one of the most strategic areas of the global energy transition:

• A prestigious academic position at FEUP, a reference engineering school in renewable and offshore energy.
• Integration within INESC TEC’s ecosystem of excellence, with access to advanced infrastructure and multidisciplinary teams in engineering, sensing, data science, robotics, and digital technologies.
• Direct collaboration with Ocean Winds, one of the world’s leading offshore wind developers, enabling the validation and application of results in real and future assets.
• Integration within the INESCTEC.OCEAN Centre of Excellence, benefiting from a shared strategic vision and strengthening ties with cutting-edge initiatives in marine systems and digital monitoring.
• Leadership and impact: the opportunity to build your own research programme, supervise master’s and doctoral students, and establish yourself as an international reference in the field.
• A highly competitive remuneration and benefits package, designed to attract top specialists worldwide: negotiable salary supplement, annual performance-based bonus, health insurance, coverage of travel/subsistence expenses, and a dedicated budget for building and training the research team.

AE2026-0280

INESC TEC is opening a call for the awarding of 1 PhD Research Grants (BI), intended for carrying out R&D activities by students enrolled in a doctoral program in the field of Electrical Engineering or related field, under the FCT Research Grants Regulation (RBI), the Research Fellowship Holder Statute (EBI) and INESC TEC Grant Regulations.

The grants will be funded by the Foundation for Science and Technology (FCT) under the Collaboration Protocol for the Funding of the Multiannual Plan of Research Grants for Doctoral Students (reference HORIZON-WIDERA-2023-ACCESS-01), signed between FCT and INESC TEC (R&D Unit FCT No. 50014).

The call is open from 2026-10-01 until 5:00 p.m. (Lisbon time) on 2026-10-15.

The Research Grant has a duration of 12 months, as a rule, starting on 2027-01-01, renewable up to a maximum of four years (48 months). The grant cannot be awarded for periods less than three consecutive months.

The proposed research focuses on the development of on-demand communication networks based on autonomous platforms, such as unmanned aerial vehicles (UAVs/drones) and unmanned surface vehicles (USVs).

The goal is to create systems capable of autonomously deploying and adapting a communication infrastructure according to environmental conditions and user needs.

The research will explore mechanisms for perception, decision-making, and action, enabling the network to identify the surrounding context, including the number and location of client devices, obstacles, propagation conditions, and communication requirements, and to dynamically adapt the position of the platforms, the network topology, and the use of communication resources.

The work will include, in particular:

• Context perception and characterization, through the integration of information collected from the autonomous platforms, client devices, and the network itself;
• Autonomous platform positioning and control, through the development of algorithms capable of determining suitable network configurations according to the observed context;
• Adaptive network management, including association and resource-management mechanisms capable of dynamically responding to communication requirements;
• Validation through simulation and experimental platforms, and testing in representative scenarios, including activities carried out in collaboration with SINTEF Ocean in Trondheim, Norway.

The work will be carried out between INESC TEC in Porto, Portugal, and SINTEF Ocean in Trondheim, Norway.

The expected outcome is to contribute to the development of a new generation of autonomous networks capable of rapidly and adaptively providing connectivity and communication capacity in scenarios where existing communication infrastructure is unavailable or insufficient.

AE2026-0282

INESC TEC is opening a call for the awarding of 1 PhD Research Grants (BI), intended for carrying out R&D activities by students enrolled in a doctoral program in the field of Electrical Engineering or related field, under the FCT Research Grants Regulation (RBI), the Research Fellowship Holder Statute (EBI) and INESC TEC Grant Regulations.

The grants will be funded by the Foundation for Science and Technology (FCT) under the Collaboration Protocol for the Funding of the Multiannual Plan of Research Grants for Doctoral Students (reference HORIZON-WIDERA-2023-ACCESS-01), signed between FCT and INESC TEC (R&D Unit FCT No. 50014).

The call is open from 2026-10-01 until 5:00 p.m. (Lisbon time) on 2026-10-15.

The Research Grant has a duration of 12 months, as a rule, starting on 2027-01-01, renewable up to a maximum of four years (48 months). The grant cannot be awarded for periods less than three consecutive months.

The proposed research focuses on the development of communication systems based on the semantic communications paradigm for long-range and/or capacity-constrained scenarios, exploring communication technologies characterized by significant limitations in bandwidth, data rate, or resource availability, such as HF,
LoRaWAN, and underwater acoustic links. The goal is to develop mechanisms capable of transmitting information efficiently by prioritizing its semantic content and the information that is most relevant to the application, rather than reproducing the original data in full.

The research will explore techniques for the semantic representation, compression, transmission, and reconstruction of information, leveraging artificial intelligence models and generative AI techniques.

The aim is to dynamically adapt the transmitted content to the characteristics of the communication channel, the available communication resources, and the application requirements, enabling the transmission of different types of information, such as text, images, audio, video, or sensor data, over highly capacity-constrained links.

The work will include, in particular:

• Semantic representation and compression of information, through the development and evaluation of mechanisms capable of identifying, selecting, and representing the information that is most relevant to the application;
• Semantic transmission over long-range and/or low-data-rate communication technologies, including the adaptation of transmission mechanisms to the characteristics of different communication media and technologies, particularly HF, LoRaWAN, and underwater acoustic communications;
• Information reconstruction and recovery at the receiver, exploring artificial intelligence models and generative AI techniques to recover the transmitted content and improve robustness against losses, errors, and channel limitations;
• Evaluation and validation through simulation and experimental platforms, as well as testing over real communication systems, considering different propagation environments, available capacities, and types of content, including activities carried out in collaboration with SINTEF Ocean in Trondheim, Norway.

The work will be carried out between INESC TEC in Porto, Portugal, and SINTEF Ocean in Trondheim, Norway.

The expected outcome is to contribute to the development of a new generation of efficient, adaptive, and robust semantic communication systems for communication-constrained environments, including maritime and underwater scenarios, where conventional technologies face significant limitations in coverage, bandwidth, data rate, and availability.

AE2026-0284

INESC TEC is opening a call for the awarding of 1 PhD Research Grants (BI), intended for carrying out R&D activities by students enrolled in a doctoral program in the field of Electrical and Computer Engineering, under the FCT Research Grants Regulation (RBI), the Research Fellowship Holder Statute (EBI) and INESC TEC Grant Regulations.

The grants will be funded by the Foundation for Science and Technology (FCT) under the Collaboration Protocol for the Funding of the Multiannual Plan of Research Grants for Doctoral Students (reference HORIZON-WIDERA-2023-ACCESS-01), signed between FCT and INESC TEC (R&D Unit FCT No. 50014).

The call is open from 2026-10-01 until 5:00 p.m (Lisbon time) on 2026-10-15.

The Research Grant has a duration of 12 months, as a rule, starting on 2027-01-01, renewable up to a maximum of four years (48 months). The grant cannot be awarded for periods less than three consecutive months.

The present work aims to develop an integrated methodology for the inspection of offshore wind turbines using an unmanned VTOL (Vertical Take-Off and Landing) aerial platform, combining vision systems, thermography, LiDAR, and tomography-based techniques.

One of the central aspects of the work will be the development of hybrid inspection methods that exploit, in a complementary manner, the characteristics of fixed-wing aircraft and multirotor platforms. The objective is to benefit from the greater endurance, speed, and energy efficiency of fixed-wing flight, while combining these advantages with the hovering capability, high manoeuvrability, and positioning accuracy of a quadrotor-type platform.

The methodology should enable the flight mode to be adapted to the different stages of the inspection process, using fixed-wing operation for transit, approach, and large-scale survey tasks, and multirotor operation for high-precision local inspections near the blades, tower, and nacelle.

The proposed solution should also be robust to GNSS degradation or loss of positioning quality, which may occur during operations close to large structures. For this purpose, a state estimator will be developed to fuse information from Visual-Inertial Odometry, LiDAR, and other navigation sensors, improving the relative positioning of the VTOL with respect to the wind turbine and ensuring greater accuracy, continuity, and safety during inspection operations.

The different sensing systems should be integrated to support the detection and characterisation of surface, thermal, geometric, and internal defects. It will also be necessary to develop trajectory planning, positioning, and data acquisition strategies capable of reconciling sensor requirements with the aerodynamic and operational constraints of the platform.

A key requirement will be to minimize, as much as possible, the period during which the nacelle must remain stopped or locked. To this end, fast and adaptive inspection strategies should be investigated, combining global surveys with detailed inspections focused only on identified regions of interest.

The work should culminate in the definition and validation of a multimodal inspection methodology based on a hybrid VTOL platform, including operational modes, robust state estimation, trajectory planning, sensor integration, data acquisition and fusion, and criteria for assessing the structural condition of the wind turbine components.

AE2020-0285

INESC TEC is opening a call for the awarding of 1 PhD Research Grants (BI), intended for carrying out R&D activities by students enrolled in a doctoral program in the field of Electrical and Computer Engineering, under the FCT Research Grants Regulation (RBI), the Research Fellowship Holder Statute (EBI) and INESC TEC Grant Regulations.

The grants will be funded by the Foundation for Science and Technology (FCT) under the Collaboration Protocol for the Funding of the Multiannual Plan of Research Grants for Doctoral Students (reference HORIZON-WIDERA-2023-ACCESS-01), signed between FCT and INESC TEC (R&D Unit FCT No. 50014).

The call is open from 2026-10-01 until 5:00 p.m (Lisbon time) on 2026-10-15.

The Research Grant has a duration of 12 months, as a rule, starting on 2027-01-01, renewable up to a maximum of four years (48 months). The grant cannot be awarded for periods less than three consecutive months.

The present work aims to develop a multimodal and distributed system for the security and surveillance of offshore wind farms, based on a multi-vehicle architecture capable of coordinated operation across different domains: underwater, surface, and aerial.

The proposed solution should integrate different autonomous robotic platforms, namely underwater vehicles, surface vehicles, and unmanned aerial vehicles, organized into different surveillance layers. Each layer should provide complementary capabilities for perception, detection, and tracking of events or potential threats, enabling persistent and cooperative monitoring of the offshore infrastructure and its surrounding environment.

One of the main objectives will be the development of a distributed architecture for cooperation and information fusion among the different vehicles, allowing observations from heterogeneous sensors and multiple viewpoints to be combined. The methodology should support the detection, association, validation, and classification of potential threats through the correlation of information collected by the different robotic agents, thereby increasing system robustness and reducing the probability of false alarms.

The multimodal solution should also enable the construction and dynamic updating of a Digital Twin representing the operational situation and the threats identified within the offshore wind farm. This digital model should aggregate spatial, temporal, and semantic information provided by the different vehicles, allowing the representation of the location, trajectory, behaviour, confidence level, and observation history associated with each detected entity or event.

Strategies for multi-robot coordination, mission planning, dynamic reconfiguration of the surveillance network, and task allocation according to the nature and evolution of the identified threats should also be investigated. The architecture should take into account communication constraints, energy autonomy, sensor availability, and adverse environmental conditions characteristic of offshore operations.

The work should culminate in the definition and validation of a multimodal, distributed, and multi-vehicle architecture for the surveillance and security of offshore wind farms, including mechanisms for cooperative threat detection and validation, data fusion, coordination among robotic platforms, and the generation of a dynamic Digital Twin to support situational awareness and decision-making.

AE2020-0286

INESC TEC is opening a call for the awarding of 1 PhD Research Grants (BI), intended for carrying out R&D activities by students enrolled in a doctoral program in the field of Electrical and Computer Engineering, under the FCT Research Grants Regulation (RBI), the Research Fellowship Holder Statute (EBI) and INESC TEC Grant Regulations.

The grants will be funded by the Foundation for Science and Technology (FCT) under the Collaboration Protocol for the Funding of the Multiannual Plan of Research Grants for Doctoral Students (reference HORIZON-WIDERA-2023-ACCESS-01), signed between FCT and INESC TEC (R&D Unit FCT No. 50014).

The call is open from 2026-10-01 until 5:00 p.m (Lisbon time) on 2026-10-15.

The Research Grant has a duration of 12 months, as a rule, starting on 2027-01-01, renewable up to a maximum of four years (48 months). The grant cannot be awarded for periods less than three consecutive months.

Autonomous navigation in GNSS-denied environments remains a major challenge for robotic systems due to localisation drift, perceptual degradation, limited situational awareness, and communication constraints. These challenges become particularly relevant in ocean environments, where reliable GNSS coverage may be unavailable or degraded, environmental conditions are highly dynamic, and autonomous platforms must operate for extended periods with limited external infrastructure.

This PhD scholarship will focus on developing cooperative autonomous navigation methods for teams of robotic platforms operating in GNSS-denied environments, with particular emphasis on applications in ocean and maritime settings. The research will investigate how multiple autonomous agents can cooperate by sharing complementary sensing and localisation information to improve navigation accuracy, robustness, and resilience.

The research will explore multimodal perception and localisation architectures that combine sensors such as cameras, inertial measurement units, acoustic sensing, radar, and inter-agent ranging technologies. Depending on the operational scenario, additional sensing modalities relevant to maritime environments may also be considered. Sensor fusion techniques will be developed to provide reliable localisation, mapping, obstacle detection, and situational awareness under challenging conditions, including changing illumination, adverse weather, wave-induced motion, limited visibility, and sparse environmental features.

A central research topic will be the development of distributed and cooperative localisation and SLAM frameworks. These methods will enable multiple autonomous platforms to exchange local observations, relative
measurements, and map information in order to maintain consistent estimates of their positions and surroundings without relying on GNSS or fixed external infrastructure.

The PhD will also investigate cooperative navigation strategies involving heterogeneous robotic systems, potentially including unmanned aerial vehicles (UAVs), autonomous surface vehicles (ASVs), and autonomous underwater vehicles (AUVs). Cooperation between aerial, surface, and underwater platforms can provide complementary sensing capabilities and enable persistent
monitoring, inspection, mapping, and exploration of complex ocean environments.

From a scientific and technological perspective, the proposed methods will be evaluated not only in terms of localisation and navigation accuracy, but also with respect to computational efficiency, scalability, communication requirements, robustness, and real-time feasibility. Algorithms will therefore be designed with deployment on embedded and edge computing platforms in mind, considering the energy and computational constraints of autonomous robotic systems.

Learning-based and self-supervised approaches may also be investigated to improve perception, sensor fusion, and adaptation to changing environmental conditions. Such methods can enable autonomous systems to adjust their navigation strategies to different sensing conditions and operational scenarios while reducing their dependence on extensive manually labelled datasets.

The proposed approaches will be validated through simulation and experimental trials involving realistic GNSS-denied scenarios, with a particular focus on ocean and maritime applications. Potential applications include marine environmental monitoring, offshore infrastructure inspection, search and rescue, oceanographic data collection, cooperative exploration, and persistent surveillance.

AE2026-0287

INESC TEC is opening a call for the awarding of 1 PhD Research Grants (BI), intended for carrying out R&D activities by students enrolled in a doctoral program in the field of Physics Engineering, under the FCT Research Grants Regulation (RBI), the Research Fellowship Holder Statute (EBI) and INESC TEC Grant Regulations.

The grants will be funded by the Foundation for Science and Technology (FCT) under the Collaboration Protocol for the Funding of the Multiannual Plan of Research Grants for Doctoral Students (reference HORIZON-WIDERA-2023-ACCESS-01), signed between FCT and INESC TEC (R&D Unit FCT No. 50014).

The call is open from 2026-10-01 until 5:00 p.m. (Lisbon time) on 2026-10-15.

The Research Grant has a duration of 12 months, as a rule, starting on 2026-12-01, renewable up to a maximum of four years (48 months). The grant cannot be awarded for periods less than three consecutive months.

The proposed research focuses on advanced multimodal spectral and 3D sensing for underwater environments. It will address the influence of absorption, scattering, turbidity, illumination and acquisition geometry on optical measurements, while developing robust approaches for underwater material characterization.

The project will combine spectroscopy and spectral imaging with conventional imaging and 3D information. Depending on the application, techniques may include hyperspectral imaging, Raman spectroscopy, LIBS and/or XRF, together with calibration, multimodal co-registration, data fusion and machine-learning methods.

The research will involve several main tasks:

• Underwater Sensor Development and Calibration — Characterize underwater optical effects and adapt or develop sensing configurations, including illumination, detection, optical interfaces, housings and acquisition electronics.
• Multimodal and 3D Integration — Co-register and combine spectroscopic, spectral imaging, conventional imaging and 3D data acquired over common regions of interest.
• Data Processing and Machine Learning — Develop calibration, correction, data-fusion and machine-learning methods for material identification, mapping and information transfer between sensing modalities.
• Experimental Validation — Perform controlled laboratory and underwater tests followed by validation under representative conditions and, where feasible, integration with ROVs or AUVs.

The expected outcome is a validated multimodal underwater sensing framework combining spectral, spatial and 3D information. Applications may include underwater cultural heritage, marine and geological materials, environmental monitoring and underwater inspection.

AE2026-0291

INESC TEC is opening a call for the awarding of 1 PhD Research Grant (BI), intended for carrying out R&D activities by students enrolled in a doctoral program in the field of Electrical and Computer Engineering, under the FCT Research Grants Regulation (RBI), the Research Fellowship Holder Statute (EBI) and INESC TEC Grant Regulations.

The grants will be funded by the Foundation for Science and Technology (FCT) under the Collaboration Protocol for the Funding of the Multiannual Plan of Research Grants for Doctoral Students (reference HORIZON-WIDERA-2023-ACCESS-01), signed between FCT and INESC TEC (R&D Unit FCT No. 50014).

The call is open from 2026-10-01 until 5:00 p.m. (Lisbon time) on 2026-10-15.

The Research Grant has a duration of 12 months, as a rule, starting on 2027-01-01, renewable up to a maximum of four years (48 months). The grant cannot be awarded for periods less than three consecutive months.

The doctoral research will focus on the development of advanced methodologies for long-range and long-endurance autonomous underwater navigation, exploiting seabed morphology, infrastructure geometry, and other natural or artificial elements of the environment as references for localization.

The research will aim to reduce reliance on external positioning infrastructure and limit the accumulation of error inherent in inertial navigation over extended missions, particularly in GPS-denied scenarios and environments with limited availability of artificial references. The objective is to develop solutions capable of maintaining high levels of navigation accuracy and consistency over long trajectories by exploiting environmental information acquired throughout the mission.

The work will consider the integration of navigation sensors with acoustic and, where appropriate, optical sensors, enabling persistent environmental features to be identified and reused, such as seabed morphological variations, offshore structures, cables, pipelines, foundations, harbour infrastructure, and other relevant geometries. These references will be exploited to provide periodic corrections to the position estimate and reduce the growth of uncertainty over time.

A central component of the research will be the development of methods capable of operating over missions covering large spatial extents, where navigation accuracy depends on the ability to recognise previously observed references, associate observations with existing maps or maps constructed during the mission and consistently manage accumulated uncertainty.

The objectives of the work include:

• Developing methods for representing the underwater environment that are suitable for long-range navigation, using bathymetric maps, three-dimensional representations, point clouds, and geometric or semantic descriptors.
• Investigating robust methodologies for the detection, extraction, and association of environmental features, capable of operating under varying viewpoints, resolutions, and acquisition conditions.
• Developing terrain- and infrastructure-based localization algorithms that relate observations acquired by the vehicle to maps available beforehand or constructed during the mission itself.
• Studying strategies for periodic correction of navigation error through the recognition of previously observed areas, matching of persistent features, and identification of suitable environmental references.
• Developing sensor-fusion and state-estimation methodologies, with particular emphasis on the propagation and management of uncertainty during long-duration missions.
• Investigating criteria for selecting the most informative environmental references, prioritising observations that maximise the reduction of navigation uncertainty over long trajectories.
• Exploring, where relevant, information obtained from other robotic systems or mobile infrastructures as an additional source of navigation correction or validation, without assuming permanently multi-robotic operation.
• Evaluating the performance of the developed methodologies in long-range missions, considering accumulated positioning accuracy, robustness, navigation-solution availability, computational requirements, and real-time operation.
• Implementing and experimentally validating the developed solutions through a progressive evaluation process involving simulation, trials in controlled environments, and field campaigns using underwater robotic platforms.

The work is expected to contribute to the development of underwater systems capable of undertaking increasingly long and autonomous missions by using the environment itself as a source of information for controlling navigation error and reducing reliance on external positioning infrastructure.

AE2026-0203

INESC TEC is opening a call for the awarding of 1 PhD Research Grants (BI), intended for carrying out R&D activities by students enrolled in a doctoral program in the field of Maritime Infrastructures / Offshore Renewable Energy, under the FCT Research Grants Regulation (RBI), the Research Fellowship Holder Statute (EBI) and INESC TEC Grant Regulations.

The grants will be funded by the Foundation for Science and Technology (FCT) under the Collaboration Protocol for the Funding of the Multiannual Plan of Research Grants for Doctoral Students (reference HORIZON-WIDERA-2023-ACCESS-01), signed between FCT and INESC TEC (R&D Unit FCT No. 50014).

The call is open from 2026-10-01 until 5:00 p.m. (Lisbon time) on 2026-10-15.

The grant has a duration of 12 months, as a rule, starting on 2026-12-01, renewable up to a maximum of four years (48 months). The grant cannot be awarded for periods less than three consecutive months.

The PhD candidate’s work plan aims to develop innovative mooring and anchoring solutions for floating offshore wind turbines, integrating advanced structural health monitoring (SHM) systems. The work includes research into new anchoring concepts adaptable to different soil types, the development of smart mooring cables with embedded sensors, and the integration of structural monitoring data for performance optimization and predictive maintenance.

The plan also includes experimental validation in an ocean laboratory and, if possible, in collaboration with industrial partners. The work to be carried out will include experiments in an ocean laboratory, participation in structural monitoring campaigns, and training in advanced numerical simulation and data analysis tools.

The candidate will also have a training and capacity-building period to be defined at SINTEF OCEAN in Trondheim (Norway). The supervisory team is composed of Filipe Manuel Rodrigues Leite Magalhães (FEUP) and Diogo Neves (INESCTEC), together with co-supervisors from INESCTEC and SINTEF Ocean (Norway), as outlined in the work plan.

The main objective of this PhD is to develop and validate innovative mooring and anchoring systems, with integrated structural monitoring, to increase reliability and reduce maintenance costs of floating offshore wind turbines.

The specific objectives include:

• Investigate and develop new concepts of hybrid anchoring and smart mooring cables.
• Integrate structural sensors into mooring systems for real-time monitoring.
• Develop numerical models to simulate the dynamic behavior of mooring and anchoring systems under different environmental conditions.
• Analyse and optimize structural performance and predictive maintenance based on monitoring data.
• Validate the proposed solutions through laboratory tests and, if possible, in real environments.
• Contribute to the digitalisation and increased reliability of offshore wind turbines.

AE2026-0202

INESC TEC is opening a call for the awarding of 1 PhD Research Grant (BI), intended for carrying out R&D activities by students enrolled in a doctoral program in the field of Maritime Infrastructures, under the FCT Research Grants Regulation (RBI), the Research Fellowship Holder Statute (EBI) and INESC TEC Grant Regulations.

The grants will be funded by the Foundation for Science and Technology (FCT) under the Collaboration Protocol for the Funding of the Multiannual Plan of Research Grants for Doctoral Students (reference HORIZON-WIDERA-2023-ACCESS-01), signed between FCT and INESC TEC (R&D Unit FCT No. 50014).

The call is open from 2026-10-01 until 5:00 p.m. (Lisbon time) on 2026-10-15.

The research grant has a duration of 12 months, as a rule, starting on 2026-12-01, renewable up to a maximum of four years (48 months). The grant cannot be awarded for periods less than three consecutive months.

The selected applicant will be supporting researchers in the fields of knowledge described in this call, who intend to carry out research activities leading to the award of a doctoral degree. Part of the research activities must be carried out at INESC TEC, as applicable.

The main objective of the doctoral research will be to contribute to the development of an integrated monitoring and predictive maintenance system for floating wind structures, with the potential to be adapted to other types and configurations of offshore wind farms.

The specific objectives include:

• Designing and implementing an SHM architecture that integrates distributed sensors (on the turbine, tower, floater, moorings, and cables) and combines them with an advanced robotic hub for inspection and data collection in the marine environment.
• Developing data analysis methodologies and numerical modelling tools for assessing structural behaviour, identifying damage, and predicting failures, using computational simulation and time series analysis techniques.
• Contributing to the experimental validation of the system, including laboratory testing and/or in situ monitoring campaigns.
• Proposing predictive maintenance strategies based on the collected data and developed models, with the aim of optimising operations and reducing maintenance costs.
• Contributing to the development of guidelines for adapting and scaling the system to different types of floating wind platforms and large-scale wind farms.

The doctoral candidate’s work plan focuses on the development of an integrated Structural Health Monitoring (SHM) system for floating wind platforms. It encompasses a comprehensive scope, ranging from literature review and complementary training in hydrodynamics and data analysis, to the implementation and experimental validation of analysis methodologies and numerical modelling.

The training plan includes participation in specialised courses, international conferences, and internships, aiming to develop advanced skills in SHM, fluid–structure interaction, and predictive maintenance, as well as the publication of scientific papers. The ultimate goal is to contribute significantly to the safety and efficiency of offshore wind energy production.

The candidate will undertake a training and capacity-building period at SINTEF OCEAN in Trondheim, Norway. The supervisory team is composed of Paulo Rosa Santos (FEUP) and Diogo Neves (INESCTEC), together with co-supervisors from INESCTEC and SINTEF Ocean (Norway), as outlined in the work plan.

AE2026-0274

INESC TEC is now accepting grant applications to award 1 Research Grant (BI) within the scope of the project WaveSense with reference 17176 (COMPETE2030-FEDER-00865400) co-funded by the ERDF – European Regional Development Fund through Innovation and Digital Transition Program – COMPETE 2030 under the scope of Portugal 2030 and by National Funds through the FCT – Fundação para a Ciência e a Tecnologia, I.P. (Portuguese Foundation for Science and Technology).

The applicant must have a Bachelor’s degree in Physical Engineering. The grant has a duration of 6 months, starting on 2026-11-01, with the possibility of being renewed for a maximum term of one year.

Objectives:

• Conducting experimental demonstrations and optimizing various metamaterial configurations.
• Characterising fabricated structures under different surrounding media.
• Developing prototypes for characterizing optical sensors implemented on planar substrates and optical fibers.
• Designing integrated systems, including software for control, data acquisition, and analysis.
• Validating the developed detection systems under real operating conditions.

Work programme and training:

• The WaveSense project aims to develop artificially structured materials capable of generating and controlling surface electromagnetic waves for the detection of chemical, biochemical, and biological substances in water.
• The candidate will be responsible for investigating new methodologies to design a metamaterial architecture for monitoring contaminants present in water at low concentrations.

INESC TEC is now accepting grant applications to award 1 Research Grant (BI) within the scope of the project
NAU_AZUL, with reference 21164 Co-funded by ERDF – European Regional Development Fund through the
Innovation and Digital Transition Thematic Programme (COMPETE 2030) within the scope of Portugal 2030.

The grant has a duration of 6 months, starting on 2026-10-26, with the possibility of being renewed until the end of the project.

Objectives of the Research Grant:

• Broaden knowledge of the state of the art in the specific scientific field of the scholarship;
• Identify and select appropriate methods for the study in question;
• Acquire foundational knowledge in underwater vehicle navigation and control;
• Develop practical skills in algorithm modeling, simulation, and implementation;
• Contribute to R&D activities in underwater robotics within the scope of the curricular internship;
• Validate concepts and consolidate results through testing and technical documentation.

The selected applicant will be focusing on:

• Introductory study of fundamental concepts regarding underwater vehicle navigation and control;
• Development and testing of algorithms in a simulation environment and/or within embedded software;
• Support for integration and experimental validation on autonomous vehicles, in laboratory or testing settings;
• Support for the development, implementation, and testing of control algorithms for robotic platforms;
• Development of mathematical models for the analysis and processing of data obtained during trials;
• Preparation of technical documentation and progress reports, and support in the preparation of scientific
  publications;
• Collaboration with the Robotics and Autonomous Systems Center team on the project’s technical and scientific activities;
• Writing the fellowship activity report.

INESC TEC is opening a call for the awarding of 1 PhD Research Grant, intended for carrying out R&D activities by students enrolled in a doctoral program in the field of Maritime Infrastructures.

The doctoral candidate’s work plan focuses on the development of an integrated Structural Health Monitoring (SHM) system for floating wind platforms. It encompasses a comprehensive scope, ranging from literature review and complementary training in hydrodynamics and data analysis, to the implementation and experimental validation of analysis methodologies and numerical modelling. The training plan includes participation in specialised courses, international conferences, and internships, aiming to develop advanced skills in SHM, fluid–structure interaction, and predictive maintenance, as well as the publication of scientific papers. The ultimate goal is to contribute significantly to the safety and efficiency of offshore wind energy production.

The candidate will undertake a training and capacity building period at SINTEF OCEAN in Trondheim, Norway. The supervisory team is composed of Paulo Rosa Santos (FEUP) and Diogo Neves (INESC TEC), together with co-supervisors from INESC TEC and SINTEF Ocean (Norway), as outlined in the work plan.

The main objective of the doctoral research will be to contribute to the development of an integrated monitoring and predictive maintenance system for floating wind structures, with the potential to be adapted to other types and configurations of offshore wind farms. The specific objectives include:

• Designing and implementing an SHM architecture that integrates distributed sensors (on the turbine, tower, floater, moorings, and cables) and combines them with an advanced robotic hub for inspection and data collection in the marine environment.;
• Developing data analysis methodologies and numerical modelling tools for assessing structural behaviour, identifying damage, and predicting failures, using computational simulation and time series analysis techniques;
• Contributing to the experimental validation of the system, including laboratory testing and/or in situ monitoring campaigns;
• Proposing predictive maintenance strategies based on the collected data and developed models, with the aim of optimising operations and reducing maintenance costs;
• Contributing to the development of guidelines for adapting and scaling the system to different types of floating wind platforms and large-scale wind farms.

INESC TEC is opening a call for the awarding of 1 PhD Research Grant, intended for carrying out R&D activities by students enrolled in a doctoral program in the field of Maritime Infrastructures / Offshore Renewable Energy.

The PhD candidate’s work plan aims to develop innovative mooring and anchoring solutions for floating offshore wind turbines, integrating advanced structural health monitoring (SHM) systems. The work includes research into new anchoring concepts adaptable to different soil types, the development of smart mooring cables with embedded sensors, and the integration of structural monitoring data for performance optimization and predictive maintenance.

The plan also includes experimental validation in an ocean laboratory and, if possible, in collaboration with industrial partners. The work to be carried out will include experiments in an ocean laboratory, participation in structural monitoring campaigns, and training in advanced numerical simulation and data analysis tools. The candidate will also have a training and capacity-building period to be defined at SINTEF OCEAN in Trondheim (Norway). The supervisory team is composed of Filipe Manuel Rodrigues Leite Magalhães (FEUP) and Diogo Neves (INESC TEC), together with co-supervisors from INESC TEC and SINTEF Ocean (Norway), as outlined in the work plan.

The main objective of this PhD is to develop and validate innovative mooring and anchoring systems, with integrated structural monitoring, to increase reliability and reduce maintenance costs of floating offshore wind turbines. The specific objectives include:

• Investigate and develop new concepts of hybrid anchoring and smart mooring cables;
• Integrate structural sensors into mooring systems for real-time monitoring;
• Develop numerical models to simulate the dynamic behavior of mooring and anchoring systems under different environmental conditions;
• Analyze and optimize structural performance and predictive maintenance based on monitoring data;
• Validate the proposed solutions through laboratory tests and, if possible, in real environments;
• Contribute to the digitalization and increased reliability of offshore wind turbines.

INESC TEC is awarding a PhD Research Grant in Computer Science.

The selected applicant will be working on the integration of Virtual Choreographies into Digital Twins ecosystem in complex ocean environments. Some of the main tasks also include:

• Conduct a comprehensive literature review on Virtual Choreographies (VCs), Digital Twins (DTs), FAIR data infrastructures, visualisation in structural health monitoring (SHM), and information system architectures,
  leading to a semantic model prototype and initial publications;
• Design and develop an ontology-driven orchestration model linking VC behaviours to digital twin entities,
  ensuring alignment with cloud-native ingestion and storage technologies;
• Design a multiplatform visualisation strategy to guarantee interoperability across different digital twin
  environments;
• Implement a cross-platform visualisation engine capable of rendering VC instances in real time,
  complemented by interactive dashboards for predictive maintenance and anomaly detection;
• Conduct pilot user studies to evaluate usability, effectiveness, and decision-support impact of the developed visualisation tools;
• Integrate outcomes into an operational platform and perform large-scale validation with stakeholders to
  assess performance and applicability;
• Disseminate results through peer-reviewed journals, leading conferences, and international standardisation
  forums, consolidating contributions into the doctoral thesis.

INESC TEC is inviting for applications for a Business Development Expert.

The selected applicant will be working in the Business Development area of INESC TEC and the INESCTEC.OCEAN Centre of Excellence, being responsible for:

• Analysis of key public policies and relevant EU and national instruments for the development of the oceantechnology sector, and identification of funding opportunities;
• Mapping of relevant ecosystem stakeholders, including their characterization and positioning regarding how they may participate in the project’s animation and entrepreneurial discovery process;
• Study of value chains in related sectors to identify major gaps and assess how ocean technologies can help
  address those gaps;
• Support in organizing workshops, focus groups, and seminars involving stakeholders, aimed at needs assessment, opportunity identification, and the design of projects and actions that address identified needs;
• Support for INESC TEC’s participation in projects—namely those under the Atlantic Area Programme, the
  Regional Smart Specialisation Platform, the Regional Innovation Valley—and for the submission of
  applications to publicly funded programmes;
• Support in organizing and participating in national and international events for the INESCTEC.OCEAN project, including identifying and selecting relevant events, defining participation formats, and representing the project at these events;
• Contribution to project management by assisting in the collection and processing of relevant information for monitoring purposes.

The recruited researcher will carry out applied and fundamental research activities in the field of offshore structures hydrodynamics and technology applied to ocean-based energy generation. The work will include the numerical assessment and dynamic simulation of mooring systems, as well as the study of the hydrodynamics of offshore structures and ocean energy converters using specialised software. The researcher will also be responsible for analysing the behaviour of floating platforms, employing numerical simulation techniques and experimental analysis. The researcher will contribute to the implementation and preparation of innovation and technological development projects directly related to the offshore maritime industry. Duties will also include conducting metocean studies and analysing metoceanographic data and their application in the design and operation of structures, as well as the analysis and development of solutions for subsea structures, including submarine cables and other subsea equipment.

The doctoral candidate’s work plan focuses on the development of an integrated Structural Health Monitoring (SHM) system for floating wind platforms. It encompasses a comprehensive scope, ranging from literature review and complementary training in hydrodynamics and data analysis, to the implementation and experimental validation of analysis methodologies and numerical modelling. The training plan includes participation in specialised courses, international conferences, and internships, aiming to develop advanced skills in SHM, fluid–structure interaction, and predictive maintenance, as well as the publication of scientific papers. The ultimate goal is to contribute significantly to the safety and efficiency of offshore wind energy production. The candidate will undertake a training and capacity-building period at SINTEF OCEAN in Trondheim, Norway. The supervisory team is composed of Paulo Rosa Santos (FEUP) and Diogo Neves (INESCTEC), together with co-supervisors from INESCTEC and SINTEF Ocean (Norway), as outlined in the work plan.

The PhD candidate’s work plan aims to develop innovative mooring and anchoring solutions for floating offshore wind turbines, integrating advanced structural health monitoring (SHM) systems. The work includes research into new anchoring concepts adaptable to different soil types, the development of smart mooring cables with embedded sensors, and the integration of structural monitoring data for performance optimization and predictive maintenance. The plan also includes experimental validation in an ocean laboratory and, if possible, in collaboration with industrial partners. The work to be carried out will include experiments in an ocean laboratory, participation in structural monitoring campaigns, and training in advanced numerical simulation and data analysis tools. The candidate will also have a training and capacity-building period to be defined at SINTEF OCEAN in Trondheim (Norway). The supervisory team is composed of Filipe Manuel Rodrigues Leite Magalhães (FEUP) and Diogo Neves (INESCTEC), together with co-supervisors from INESCTEC and SINTEF Ocean (Norway), as outlined in the work plan.

The selected candidate will join the legal support team and the INESCTEC.OCEAN project, strengthening the public procurement area. They will be responsible for:

• Analyze procedures for expenditure on goods and services.
• Initiating the contract formation procedures necessary for contracting goods, services, and works contracts.
• Preparing information, procedural documents, reports, and communications.
• Initiating direct award procedures, prior consultation, limited tender by prior qualification, public tender (national and international), and excluded contracting.
• Public procurement procedures through public procurement platforms, such as AcinGov and Anogov.
• Assist in responding to public procurement procedures as the contracting entity.
• Be part of procedure juries.
• Ensure the external reporting relationships legally required in matters of public procurement. Propose rules and draft standards to harmonize the implementation of procedures for procuring goods and services as defined by legislation.
• Perform any other duties assigned to them.