PhD Position AI Powered Methods and Models for Multi-Modal Assessment of Air Pollution

PhD Position AI Powered Methods and Models for Multi-Modal Assessment of Air Pollution

Are you passionate about applying AI and inverse modelling to atmospheric models? Join the PhD project at TU Delft within the ExpACT project!

Job description

Energy- and transport-transitions aimed at reducing the CO2 emissions will bring changes to the pollutants and chemical composition in the atmosphere. Given the transitions are likely inducing new unknown pollutants, their health impact to human beings under long time exposure need to be modelled and understood. In this PhD project at TUDelft, in close collaboration with TNO, you will work on the development of methods and models to better assess and predict the exposure of people to air pollutants. It is envisioned to combine modelling using AI and data assimilation (DA) techniques with a chemistry transport model (LOTOS-EUROS). Since interpretability and trustworthiness are key, it is essential to align these models with physical laws and domain knowledge—ensuring they not only generate accurate predictions, but also reflect the underlying dynamics of the systems they aim to model, thus going beyond a purely data-driven approach.

In this PhD project, you will explore how create and improve models for particulate matter, explicitly linking the pollution to various sources regions and source categories at high spatial resolution. This involves:

• Further development of the existing foundation models for air pollutions by including physical knowledge.
• Integrating AI and DA methods for inverse modelling of chemical composition of particulate matter.
• Making fast and accurate tools that link emissions to exposure for policy support, based on the above.
• Designing optimum measurement strategies for specific components and sources, based on the above.

Join our passionate and collaborative research team.

Your home base will be the Mathematical Physics group in the Delft Institute of Applied Mathematics at TU Delft. You will be supervised by Prof.dr.ir. H.X. Lin and Dr. A.M.M. Manders-Groot and collaborate closely with experts at TU Delft and TNO in atmospheric modelling, AI, DA and inverse modelling. You’ll be working in a friendly and interdisciplinary environment, alongside fellow PhD students, and research staff both at TU Delft and TNO.

What makes this position exciting, unique, and impactful?

• You’ll work on a socially relevant topic: air pollution is an important issue for health, accurate modelling and forecast ability can help the society to take effective measures to save human lives, and reduce environmental and ecological damages.
• The combination of AI foundation models and DA methods is a new research direction. There are many challenging elements, you will explore and contribute to this cutting-edge technology.
• You’ll have plenty of room for initiative and interdisciplinary collaboration with experts at the atmospheric modelling, AI, inverse modelling and DA.

Job requirements

What makes you a great fit?

We’re looking for a motivated and curious candidate who is eager to contribute to interdisciplinary research at the intersection of AI and climate science. Ideally, you have:

• A Master’s degree (or are close to finishing one) in Applied Mathematics, Computational Science and Engineering, Atmospheric Physics or Chemistry, Artificial Intelligence, or a closely related field.
• A solid theoretical understanding of Mathematical Modelling and Numerical Models.
• Some experience with Data Assimilation, Machine Learning and Deep Learning.
• Strong programming skills—preferably in Python—and hands-on experience with machine learning frameworks and tools.
• The ability to work independently with creativity and initiative, as well as collaboratively across diverse disciplines (including atmospheric modelling, AI models).
• Strong interpersonal and communication skills, and a collaborative mindset.
• Proficiency in English, both spoken and written.

We welcome candidates from all backgrounds. Diversity makes us stronger – no matter who you are or where you come from, you are welcome at EEMCS.

TU Delft (Delft University of Technology)

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!

Faculty Electrical Engineering, Mathematics and Computer Science

The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) brings together three scientific disciplines. Combined, they reinforce each other and are the driving force behind the technology we all use in our daily lives. Technology such as the electricity grid, which our faculty is helping to make completely sustainable and future-proof. At the same time, we are developing the chips and sensors of the future, whilst also setting the foundations for the software technologies to run on this new generation of equipment – which of course includes AI. Meanwhile we are pushing the limits of applied mathematics, for example mapping out disease processes using single cell data, and using mathematics to simulate gigantic ash plumes after a volcanic eruption. In other words: there is plenty of room at the faculty for ground-breaking research. We educate innovative engineers and have excellent labs and facilities that underline our strong international position. In total, more than 1000 employees and 4,000 students work and study in this innovative environment.

Conditions of employment

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 € 2901 per month in the first year to € 3707 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.

Will you need to relocate to the Netherlands for this job? TU Delft is committed to make your move as smooth as possible! The HR unit, Coming to Delft Service, offers information on their website to help you prepare your relocation. In addition, Coming to Delft Service organises events to help you settle in the Netherlands, and expand your (social) network in Delft. A Dual Career Programme is available, to support your accompanying partner with their job search in the Netherlands.

Additional information

If you would like more information about this vacancy or the selection procedure, please contact Prof.dr.ir. H.X.Lin via h.x.lin@tudelft.nl and Dr. A.M.M. Manders-Groot via astrid.manders@tno.nl