MSc thesis assignment: Machine Learning Fusion of Sentinel 2 and ICESat-2 data for Satellite Derived Bathymetry (SDB)
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MSc thesis assignment: Machine Learning Fusion of Sentinel 2 and ICESat-2 data for Satellite Derived Bathymetry (SDB)
Contributing to a one of the most innovative developments in coastal mapping: creating a fully spaceborne bathymetry solution that fuses ICESat2 LiDAR with Sentinel2 multispectral imagery - that is what you will do as a graduation intern at Haskoning. In this assignment, you combine scientific research with direct engineering impact: developing a scalable tool for mapping shallow-water depths worldwide, you work at the forefront of a promising methodology and deliver a result our team can put to immediate use
What you will do as a MSc graduation intern
Haskoning already has strong in-house expertise in Satellite-Derived Bathymetry (SDB), but we would like you to focus on a promising new direction in this field. This graduation project centers on a machine-learning approach that predicts shallow-water bathymetry by training Sentinel-2 imagery with depth points derived from ICESat-2 photons. This emerging method offers the potential to produce accurate depth estimates without relying on costly in-situ surveys and is increasingly supported by recent scientific literature.
Main responsibilities:
- Investigate the scientific background of SDB, ICESat2 photon bathymetry, and ML based optical depth retrieval.
- Develop machinelearning models to predict bathymetry from multispectral inputs, informed by literature (e.g., Random Forest, SVM, Neural Networks).
- Produce insights on the applicability, accuracy limits, and scalability of the method for engineering use cases.
We encourage you to bring your own academic perspective and critical thinking to this project. As a starting point, we suggest the following direction:"
How can Sentinel2 multispectral imagery and ICESat2 LiDAR bathymetry be fused using machine learning to produce accurate, scalable, and engineering ready SatelliteDerived Bathymetry?
This could include:
- Implementing a workflow which can extract and process ICESat2 data and Sentinel-2 data (Haskoning already has scripts for this that could be used for inspiration).
- Training ML regressions models to capture the relationship between optical reflectance and depth
- Testing the method in one or more coastal pilot areas and assessing environmental factors influencing accuracy (e.g., turbidity, bottom type etc.).
- Delivering a prototype SDB tool / workflow that can be scaled across projects.
The deliverable is both a strong scientific thesis and if possible, a practical method that our company can adopt for future use.
Where you will work
At Haskoning, you will join an independent, employee-owned international consultancy that combines engineering, design, and consultancy services with software and technology. Our mission, "Enhancing Society Together," drives us to create a positive impact on the world.
As our new graduation intern, you will become part of the team Coastal & River, Dynamics & Design, which falls under the Advisory Group Maritime and Renewables. Our team combines deep expertise in coastal and river processes with practical engineering design to deliver robust solutions for flood risk management, coastal protection, constructing marinas, ports, and nature-based solutions for e.g. shoreline stability. In addition to modelling and design, the team develops and maintains advanced tooling. For example, Python-based workflows and reusable analytical frameworks which support efficient and standardized analyses across our company. You will work alongside colleagues who combine coastal and river engineering knowledge with remote sensing and geospatial analytics. It is an ideal environment for bridging science and engineering!
Our team mainly works from the Amersfoort, Utrecht, and Delft offices. To make your internship as enjoyable and enriching as possible, we highly recommend living as nearby as possible so you can join us in the office regularly. The more connected and engaged you are, the more rewarding your assignment will be!
What you bring
You are curious, analytical, and independent, with the drive to carry out a scientifically rigorous thesis that makes a real-world impact. You enjoy taking ownership of an innovative topic, coding data analyses, exploring complex geospatial datasets, and translating scientific insights into practical, usable tools.
Requirements:
- You are a Master's student in a relevant field (e.g., Civil/Coastal Engineering, Physical Geography, Geospatial Sciences, Remote Sensing/Earth Observation, Data Science).
- Familiarity with remote sensing concepts or eager to learn this new field (reflectance, atmospheric correction, optical properties of water).
- Basic understanding of machine learning regression methods and their role in scientific modelling.
- Interest in LiDAR, spectral imagery, and coastal environments, or willingness to learn quickly.
- Ability to work systematically, taking ownership, document results clearly, and manage a full research cycle. Or interested in learning these skills.
- And finally: Being enthusiastic about satellite data and levering this to leave a positive sustainable impact on the world!
What you can expect from us
During your internship at Haskoning, you'll have the opportunity to grow professionally in an inspiring and inclusive work environment. We offer support, guidance, and attractive conditions to help you get the most out of your internship:
- Internship allowance of €750 per month (based on a 40-hour workweek)
- Personal guidance from a dedicated mentor
- Opportunity to contribute to impactful projects
- Informal and inclusive work culture with social and sports activities
- Access to Young Haskoning, our network for young professionals, where you can join inspiring events, workshops, and informal gatherings with colleagues
Are you our new intern?
Then we would like to meet you! Click on the apply button and upload your resume and motivation letter. After receiving your application, we will contact you as soon as possible. The timeframe for the thesis we have in mind is from September 2026 to June 2027, including preparation time on the university for 3 months and joining our company for 5 to 6 months, however, this can be discussed.
The application process then consists of two interviews and possible an assessment. Are we all enthusiastic after this? Then you will receive an offer from us, and we will be happy to welcome you on board!
Do you have any questions about the role or the process? You can always contact Arend Timmer (mentor), Jelle Woerdman (mentor) or Joosje Klerks (AG student affairs manager) via LinkedIn or Arend via arend.timmer@haskoning.com.
At Haskoning, we are committed to fostering a diverse and inclusive workplace where everyone feels valued, respected, and empowered. Our mission of "Enhancing Society Together" drives us to create an environment that embraces each individual's unique background, identity, and perspective. Regardless of your experience, background, age, gender, or other personal characteristics-you are welcome here. We believe that diversity makes us stronger and that an inclusive culture gives everyone the opportunity to grow and contribute. Read more about our ED&I initiatives on our dedicated webpage.
Due to the privacy law, please submit your application via the apply button and not via email. Acquisition for this vacancy by agencies is not appreciated and offered candidates will not be taken into consideration.
Requirements
- You are a Master's student in a relevant field (e.g., Civil/Coastal Engineering, Physical Geography, Geospatial Sciences, Remote Sensing/Earth Observation, Data Science).
- Familiarity with remote sensing concepts or eager to learn this new field (reflectance, atmospheric correction, optical properties of water).
- Basic understanding of machine learning regression methods and their role in scientific modelling.
- Interest in LiDAR, spectral imagery, and coastal environments, or willingness to learn quickly.
- Ability to work systematically, taking ownership, document results clearly, and manage a full research cycle. Or interested in learning these skills.
- And finally: Being enthusiastic about satellite data and levering this to leave a positive sustainable impact on the world!
