PhD Position Satellite-derived Bathymetry using Physics-informed Machine Learning

Challenge: Generating realistic bathymetric maps at a large scale using satellite images and advanced machine learning methods.

Change: Incorporating physics into satellite-derived bathymetry methods using physics-informed machine learning (PIML). 

Impact: Supporting sustainable development to protect coastal areas from climate change and improve navigation safety.

Climate change has significantly impacted human life by increasing the frequency of natural disasters, disrupting ecosystems, and worsening coastal vulnerabilities. Bathymetry, crucial for coastal science, remains largely unknown globally despite its importance in various sectors. Coastal regions, housing 40% of the global population, face increasing vulnerability due to natural hazards and human activities. Accurate bathymetric data is also essential for navigation, dredging, and environmental management. Traditional methods like multi-beam echo-sounding are costly and time-consuming, also leaving about 50% of shallow water bodies unexplored.

By bridging this information gap, stakeholders can enhance coastal resilience and foster sustainable development. Satellite-derived bathymetry (SDB) offers an alternative, utilizing satellite images for depth retrieval. Recent advances in processing methodologies of SDB offer promising solutions. This project aims to enhance SDB accuracy through deep learning pan-sharpening and physics-informed machine learning techniques. These methods will be tested in two regions worldwide and applied to the Dutch coast, focusing on the Wadden Sea and North Sea. Your research seeks to improve SDB precision in challenging coastal environments using advanced AI. As part of your role, you will write papers, attend conferences and contribute to the reports that are the project deliverables.

As a member of our interdisciplinary Aircraft Noise and Climate Effects (ANCE) team, you will also contribute to labs and experiments and mentor master's students in their research projects. Collaborating with assistant and associate professors, lecturers, project managers, other PhD candidates, and postdocs from diverse backgrounds, we employ a wide range of model-based and empirical methods to analyse data. In particular, utilizing PIML is also integral to our approach domains. You will receive comprehensive support and training to nurture your growth as a researcher.

Learn more about Aircraft Noise and Climate Effects  

The focal point of this position is the theoretical foundation of statistical machine learning, with applications to satellite-based imageries. Candidates are required to have a strong background in mathematical statistics, signal processing, and physics-informed machine learning, coupled with a demonstrated capability to find elegant and creative solutions to challenging problems. You also should be able to work independently or in a group. In addition, you are motivated to interact with and coach master students, while enhancing your own skills and competencies.

You also have:

• An MSc in aerospace engineering, electrical engineering, computer science, applied mathematics, geodetic engineering, or other relevant subjects.
• Good analytical and programming skills such as Python.
• Solid background and knowledge in mathematical statistics.
• Knowledge and experience in data science and machine learning.
• A good command of spoken and written English

Doing a PhD at TU Delft requires English proficiency at a certain level to ensure that the candidate is able to communicate and interact well, participate in English-taught Doctoral Education courses, and write scientific articles and a final thesis. For more details please check the Graduate Schools Admission Requirements .

Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2,5 years assuming everything goes well and performance requirements are met.

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2770 per month in the first year to € 3539 in the fourth year. As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.

The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged. 

For international applicants, TU Delft has the Coming to Delft Service . This service provides information for new international employees to help you prepare the relocation and to settle in the Netherlands. The Coming to Delft Service offers a Dual Career Programme  for partners and they organise events to expand your (social) network.

Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context.

At TU Delft we embrace diversity as one of our core values  and we actively engage  to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale. That is why we invite you to apply. Your application will receive fair consideration.

Challenge. Change. Impact!

The Faculty of Aerospace Engineering at Delft University of Technology is one of the world’s most highly ranked (and most comprehensive) research, education and innovation communities devoted entirely to aerospace engineering. More than 200 science staff, around 270 PhD candidates and close to 3000 BSc and MSc students apply aerospace engineering disciplines to address the global societal challenges that threaten us today, climate change without doubt being the most important. Our focal subjects: sustainable aerospace, big data and artificial intelligence, bio-inspired engineering and smart instruments and systems. Working at the faculty means working together. With partners in other faculties, knowledge institutes, governments and industry, both aerospace and non-aerospace. Working in field labs and innovation hubs on our university campus and beyond. 

Click here  to go to the website of the Faculty of Aerospace Engineering.

Are you interested in this vacancy? Please apply no later than 31 March 2024 via the application button and upload your:

• Motivation letter (please provide detailed insights into your background, expertise, and the approach you use to address this research project).
• Detailed CV, including a list of possible scientific publications.
• Transcripts of your BSc and MSc (list of courses taken and grades - in English).
• A copy of (or link to) your MSc-thesis, as an attachment.
• A statement on English language proficiency.
• Names and contact information of at three relevant references. We will not contact references without your consent.

Please note: 

• After the first selection, video interviews will be arranged. Should further assessments be necessary, selected candidates will undergo additional activities as part of the final selection process.    
• You can apply online. We will not process applications sent by email and/or post.
• Please do not contact us for unsolicited services.

 For further information about this project and this position, you can contact Dr. Alireza Amiri-Simkooei ([email protected] ) or Prof.dr.ir. Mirjam Snellen ([email protected] ).    

A pre-employment screening can be part of the selection procedure.