PhD Candidate in Hybrid Learning-Control Methods for Autonomous Underwater Manipulation

NTNU - Norwegian University of Science and Technology

Trondheim

On-site

NOK 522,000 - 638,000

Full time

2 days ago
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Job summary

NTNU - Norwegian University of Science and Technology is seeking a PhD Candidate to develop hybrid learning–control methods for autonomous underwater manipulation. The project is part of the Norwegian Centre for Embodied AI (NCEI) and will explore safe, robust integration of learning with model-based control.

The successful candidate will work under Professor Kristin Y. Pettersen with Professor Jan Tommy Gravdahl as co-supervisor, pursue doctoral education over three years with possible

Qualifications

  • Master’s degree in cybernetics, control systems, or equivalent, with 120 credits at master's level.
  • Strong academic record with average grade equal to B or better.
  • Meets admission requirements for NTNU PhD program in relevant IT/EE faculty.
  • English proficiency if not mother tongue (TOEFL/IELTS/CAE/CPE).

Responsibilities

  • Complete doctoral education leading to the PhD degree.
  • Conduct and publish high-quality research within the framework described above.
  • Participate in international activities such as conferences and/or research stays abroad.
  • Collaborate with other researchers within the department and across departments at NTNU.
  • Supervise master’s thesis students related to the project.
  • Upon agreement with the candidate and the department, the position may be extended for teaching duties.

Skills

Marine robotics
Control systems
Machine learning

Education

Master's degree in cybernetics/controls

Job description

PhD Candidate in Hybrid Learning-Control Methods for Autonomous Underwater Manipulation

NTNU - Norwegian University of Science and Technology

Stillingstittel PhD Candidate in Hybrid Learning-Control Methods for Autonomous Underwater Manipulation

NTNU is a broad-based university with atechnical-scientific profile and a focusin professional education. The university is located in three cities with headquarters in Trondheim.

At NTNU, 9,000 employees and 43,000 students work to create knowledge for a better world.

You will find more information about working at NTNU and the application process here.

The position is for three years with the possibilityof up to one-year extension for teaching assistant duties, and is part of the Norwegian Centre for Embodied AI (NCEI), one of Norway’s six national AI centres.

The centre is recruiting outstanding researchers to advance a universal science of embodied intelligence. NCEI brings together leading robotics and AI groups with key partners from industry and the public sector to study how intelligence emerges from the interaction between body, computation, and environment, across flying, ground, and aquatic robot configurations.

Our mission is to chart a generalisable path for physical AI and transform how robot morphology and autonomy are co-designed, enabling new generations of systems tailored to their operational environments and missions. Successful candidates will join an international community with world-class facilities and strong collaborations across Norwegian universities, research institutes, industry, public agencies, and leading global institutions. We welcome motivated applicants in robotics, control, AI, machine learning, physics, and related fields, including early-stage researchers eager to contribute to this emerging scientific frontier.

About the project

The role of the PhD candidate will be to develop efficient methods for

Hybrid Learning-Control Methods for Autonomous Underwater Manipulation:Modern AI has demonstrated remarkable capabilities in learning, adaptation, planning, and decision-making. However, autonomous underwater manipulation presents challenges that remain difficult for purely data-driven methods, including safety-critical operation, uncertain environments, limited data availability, and the need for reliable performance guarantees. In this project, you will investigate how the strengths of modern machine learning can be combined with the rigorous foundations of control systems theory to create a new generation of intelligent underwater robotic systems.

The research will focus on developing hybrid learning–control architectures that integrate model-based control and planning methods with data-driven learning approaches. Potential topics include safe reinforcement learning, learning-based adaptation and control, physics-informed machine learning, learning-enhanced model predictive control, control-theoretic safety and stability guarantees for learning-enabled systems, and the integration of foundation models with autonomous robotic decision-making and control. The methods developed will be validated on advanced underwater robotic platforms performing challenging manipulation tasks such as object retrieval, inspection, intervention, and maintenance operations.

This position offers a unique opportunity to contribute to one of the most exciting frontiers in robotics and AI: combining the best of modern learning methods with the best of control systems theory. The ultimate goal is to develop autonomous underwater robots that can learn, adapt, and make intelligent decisions while retaining the reliability, robustness, and safety required for operation in complex real-world environments.

The PhD candidate will be supervised by Professor Kristin Y. Pettersen, with Professor Jan Tommy Gravdahl as co-supervisor.

Duties of the position
  • Complete your doctoral education leading to the PhD degree.
  • Conduct and publish research of high quality within the framework described above.
  • Participate in international activities such as conferences and/or research stays abroad.
  • Collaborate with other researchers within the department and across departments at NTNU.
  • Supervise master’s thesis students related to the project.
  • Upon agreementwith the candidate and the department, the position may be extended if the candidate undertakescareer-enhancing work beyond the research project, such as teaching duties.

Be prepared for changes to your work duties after employment.

Required selection criteria
  • You must have a Master's degree in cybernetics, control systems, or equivalent, with a strong training in control of marine vehicles and/or robots. Additional training in machine learning methods is an advantage. Your degree must correspond to a five-year Norwegian program, where 120 credits have been obtained at master's level. Master’s students in their final year are welcome to apply; employment will then be postponed until the master’s degree is completed.
  • You must have a strong academic background from your previous studies and have an average grade from your Master's degree study, or equivalent education, which is equal to B or better compared to NTNU's grading scale. If you do not have letter grades from previous studies, you must have an equally good academic foundation. If you have slightly weaker grades, you may be considered if you can document that you are particularly suitable for a PhD education.
  • You must fulfilthe admission requirements for the PhD program at the Faculty of Information Technology and Electrical Engineering.
  • Applicants who do not master a Scandinavian language and do not have English as mother tongue, must document English proficiency through one of the following tests: TOEFL, IELTS or Cambridge Certificate in Advanced English (CAE) or Cambridge Certificate of Proficiency in English (CPE). Minimum scores are: TOEFL: 600 (paper-based test), 92 (Internet-based test), IELTS: 6.5, with no section lower than 6.5 (only Academic IELTS test accepted), CAE or CPE certificate with a minimum score of 180.
  • Our research has civilian objectives. However, equipment restricted by export licenses and ITAR (International Traffic in Arms Regulations) are being used in the research project. Applicants who are citizens of Norway, EU, Switzerland, Australia, Japan, New Zealand, or NATO countries are eligible. Other applicants are required to provide evidence of their eligibility to work with such equipment for their application to be considered.
This is NTNU

NTNU is a broad-based university with atechnical-scientific profile and a focusin professional education. The university is located in three cities with headquarters in Trondheim.

At NTNU, 9,000 employees and 43,000 students work to create knowledge for a better world.

You will find more information about working at NTNU and the application process here.

Video: https://youtu.be/Xt-yHCN5QS0

About the position

The position is for three years with the possibilityof up to one-year extension for teaching assistant duties, and is part of the Norwegian Centre for Embodied AI (NCEI), one of Norway’s six national AI centres.

The centre is recruiting outstanding researchers to advance a universal science of embodied intelligence. NCEI brings together leading robotics and AI groups with key partners from industry and the public sector to study how intelligence emerges from the interaction between body, computation, and environment, across flying, ground, and aquatic robot configurations.

Our mission is to chart a generalisable path for physical AI and transform how robot morphology and autonomy are co-designed, enabling new generations of systems tailored to their operational environments and missions. Successful candidates will join an international community with world-class facilities and strong collaborations across Norwegian universities, research institutes, industry, public agencies, and leading global institutions. We welcome motivated applicants in robotics, control, AI, machine learning, physics, and related fields, including early-stage researchers eager to contribute to this emerging scientific frontier.

About the project

The role of the PhD candidate will be to develop efficient methods for

Hybrid Learning-Control Methods for Autonomous Underwater Manipulation:Modern AI has demonstrated remarkable capabilities in learning, adaptation, planning, and decision-making. However, autonomous underwater manipulation presents challenges that remain difficult for purely data-driven methods, including safety-critical operation, uncertain environments, limited data availability, and the need for reliable performance guarantees. In this project, you will investigate how the strengths of modern machine learning can be combined with the rigorous foundations of control systems theory to create a new generation of intelligent underwater robotic systems.

The research will focus on developing hybrid learning–control architectures that integrate model-based control and planning methods with data-driven learning approaches. Potential topics include safe reinforcement learning, learning-based adaptation and control, physics-informed machine learning, learning-enhanced model predictive control, control-theoretic safety and stability guarantees for learning-enabled systems, and the integration of foundation models with autonomous robotic decision-making and control. The methods developed will be validated on advanced underwater robotic platforms performing challenging manipulation tasks such as object retrieval, inspection, intervention, and maintenance operations.

This position offers a unique opportunity to contribute to one of the most exciting frontiers in robotics and AI: combining the best of modern learning methods with the best of control systems theory. The ultimate goal is to develop autonomous underwater robots that can learn, adapt, and make intelligent decisions while retaining the reliability, robustness, and safety required for operation in complex real-world environments.

The PhD candidate will be supervised by Professor Kristin Y. Pettersen, with Professor Jan Tommy Gravdahl as co-supervisor.

Duties of the position
  • Complete your doctoral education leading to the PhD degree.
  • Conduct and publish research of high quality within the framework described above.
  • Participate in international activities such as conferences and/or research stays abroad.
  • Collaborate with other researchers within the department and across departments at NTNU.
  • Supervise master’s thesis students related to the project.
  • Upon agreementwith the candidate and the department, the position may be extended if the candidate undertakescareer-enhancing work beyond the research project, such as teaching duties.

Be prepared for changes to your work duties after employment.

Required selection criteria
  • You must have a Master's degree in cybernetics, control systems, or equivalent, with a strong training in control of marine vehicles and/or robots. Additional training in machine learning methods is an advantage. Your degree must correspond to a five-year Norwegian program, where 120 credits have been obtained at master's level. Master’s students in their final year are welcome to apply; employment will then be postponed until the master’s degree is completed.
  • You must have a strong academic background from your previous studies and have an average grade from your Master's degree study, or equivalent education, which is equal to B or better compared to NTNU's grading scale. If you do not have letter grades from previous studies, you must have an equally good academic foundation. If you have slightly weaker grades, you may be considered if you can document that you are particularly suitable for a PhD education.
  • You must fulfilthe admission requirements for the PhD program at the Faculty of Information Technology and Electrical Engineering.
  • Applicants who do not master a Scandinavian language and do not have English as mother tongue, must document English proficiency through one of the following tests: TOEFL, IELTS or Cambridge Certificate in Advanced English (CAE) or Cambridge Certificate of Proficiency in English (CPE). Minimum scores are: TOEFL: 600 (paper-based test), 92 (Internet-based test), IELTS: 6.5, with no section lower than 6.5 (only Academic IELTS test accepted), CAE or CPE certificate with a minimum score of 180.
  • Our research has civilian objectives. However, equipment restricted by export licenses and ITAR (International Traffic in Arms Regulations) are being used in the research project. Applicants who are citizens of Norway, EU, Switzerland, Australia, Japan, New Zealand, or NATO countries are eligible. Other applicants are required to provide evidence of their eligibility to work with such equipment for their application to be considered.

PLEASE NOTE: For detailed information about what the application must contain, see paragraph “About the application”.

The appointment is to be made in accordance with NTNUs guidelines for recruitment positions and the general criteria for the position.

Preferred selection criteria
  • A solid theoretical background in nonlinear control and the control of marine vehicles or robotic systems.
  • Additional training in machine learning methods is an advantage.
  • Solid programming skills.
  • Strong skills in mathematics, excellent capacity for mathematical formalism, and ability to grasp new concepts quickly.
Personal characteristics

To successfully complete a doctoral degree (PhD), it is important that you are able to:

  • Work independently and in a structured way, set goals and make plans to achieve them.
  • Demonstrate strong analytical and communication skills, and ability to discuss and present research clearly.
  • Willingness to learn, show curiosity and a strong motivation for the subject.
  • Be open to exploring topics outside your comfort zone, generate new ideas, and engage in constructive, critical discussions with your supervisors to evaluate research ideas.
  • Perseverance and the ability to work effectively under pressure or in the face of adversity.

Emphasis will be placed on personal suitability.

We offer
  • An exciting job with an important mission in society
  • Developing tasks in a strong and international professional environment
  • Career guidance and follow-up during the PhD period
  • Open and inclusive working environment with committed colleagues
  • Working capital that can be used to implement the project
  • Mentor program as a new employee at NTNU
  • Favorable terms as a member of the Norwegian Public Service Pension Fund (SPK)

As a PhD Candidate at NTNU, you will have access to employee benefits .

Diversity

Diversity is a strength, and at NTNU we aim to be an employer that reflects the diversity in society and that makes use of the potential of the population's collective skills. Our vision is Knowledge for a better world and our values are creative, critical, constructive and respectful . We believe that an organization that is equal, diverse and gender-balanced is essential for us to achieve our goals.

We strive to attract employees with different skills, life experiences and perspectives to contribute to even better problem solving of our societal mission in research and education.

Salary and conditions

In the position of PhD Candidate, code 1017, your gross salary will normally be from NOK 580 000,- per annum depending on qualifications and seniority. A 2% statutory contribution to the State Pension Fund is deducted from the salary.

The employment period is 3 years for the doctoral work, with the possibility of up to 12 months in addition of career promotion work for the right candidate.

For employment as a PhD Candidate, it is a prerequisite that you gain admission to the PhD programme in Engineering Cybernetics within three months of your employment contract start date, and that you participate in an organized doctoral programme through out the period of employment.

As an employee at NTNU, it is important that you keep yourself up to date with academic and organizational changes and adapt to them.

For the necessary professional and social interaction, it is a prerequisite that you are physically present and available to the institution on a daily basis.

The appointment is carried out in accordance with the principles of the State Employees Act , and Export control (legislation that regulates the export of knowledge, technology and services). Candidates who, after assessment of the application and attachments, are considered to be in conflict with the criteria in the latter act, will not be able to be employed.

About the application

The attachments (including a description of your scientific work) must accompany the application as these documents form the basis of the application assessment. The documents must be in Norwegian/a Scandinavian language or English.

Please note: the application will only be assessed on the basis of the information we have received by the application deadline. Therefore, make sure that your application clearly shows how your skills and experience meet the criteria described above. The application and all attachments must be sent electronically via Jobbnorge.no. If you are invited to an interview, you must bring certified copies of certificates and diplomas upon request.

The application must include:

  • Transcripts and diplomas for Bachelor's and Master's degrees. Documentation of a completed Master's degree must be presented before taking up the position.
  • A copy of your Master's thesis, if completed. If you are currently working onyour Master's thesis, you can attach a draft of the thesis.
  • CV
  • Short letter of motivation (400 words/1 page).
  • Names and contact information of minimum 2 relevant referees.
  • For applicants who are not citizens of Norway, EU, Switzerland, Australia, Japan, New Zealand, or NATO countries,evidence of their eligibility to work with ITAR equipment must be provided.

If all, or parts, of your education has been taken abroad, we also ask you to attach documentation of the scope and quality of your entire education, both Bachelor's and Master's education, in addition to other higher education. If your institution uses “diploma supplement” (normal for most European institutions), you must attach this. A description of the documentation required can also be found here . If you already have a statement from Norwegian Directorate for Higher Education and Skills (HK-dir) , please attach this as well.

Joint work will be considered. If it is difficult to identify your contribution to joint work, you must attach a brief description of your participation.

When assessing the best qualified, we emphasize necessary qualifications such as education, experience and personal suitability. Motivation for the position, ambitions, and potential for research will also count when assessing the candidates.

NTNU recognizes a wide range of academic contributions and has committed itself to The San Francisco Declaration on Research Assessment and CoARA (responsible assessment of research and recognition of a greater breadth of academic contributions in accordance with NTNU's social mission).

General information

A public list of applicants with name, age, job title and municipality of residence is prepared after the application deadline. If you wish to be exempt from entry on the public applicant list, this must be justified. Assessment will be made in accordance with current legislation . You will be notified if the exemption is not granted.

If you have any questions about the position, please contact Professor Kristin Ytterstad Pettersen, email: kristin.y.pettersen@ntnu.no .

If you have any questions about the recruitment process, please contact HR Consultant Berit Dahl, e-mail: berit.dahl@ntnu.no .

Application deadline: 16.10.2026.

For practical information about working at NTNU, please visit this webpage.

The city of Trondheim is a modern European city with a rich cultural scene. Trondheim is the tech capital of Norway with a population of 200,000.The Norwegian welfare state, including healthcare, schools, kindergartens and overall equality, is probably the best of its kind in the world. Professional subsidized day-care for children is easily available. Furthermore, Trondheim offers great opportunities for education (including international schools) and possibilities to enjoy nature, culture and family life and has low crime rates and clean air quality.

Om bedriften

NTNU - knowledge for a better world

The Norwegian University of Science and Technology (NTNU) creates knowledge for a better world and solutions that can change everyday life.

Department of Engineering Cybernetics (ITK)

PhD Candidate in AI-Enhanced Planning in Shipbuilding Supply Chains

NTNU - Norwegian University of Science and Technology

NTNU - Norwegian University of Science and Technology

NTNU - Norwegian University of Science and Technology

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