The DAWN group at the University of Lausanne invites applications for two fully funded PhD positions at the broad intersection of atmospheric physics and artificial intelligence.
Both positions are funded for up to 5 years, including salary, research travel, equipment, and access to computing resources. The positions will be hosted within the Institute of Earth Surface Dynamics and UNIL’s Expertise Center for Climate Extremes.
All application documents (details below) must be submitted through the official UNIL application portal:
- Position 1: [Link]
To ensure full consideration, applications should be submitted by June 15, 2026 at this link. The desired start date is September 1, 2026. Applicants to Position 1 will automatically also be considered for Position 2, unless they state otherwise. - Position 2: [Link]
To ensure full consideration, applications should be submitted by September 15, 2026 at this link. The desired start date is March 1, 2027.
Outstanding applications submitted after the deadlines may be considered on a rolling basis until the positions are filled. Questions can be addressed to dawn-jobs@unil.ch.
Research scope
We are looking for curious and rigorous candidates who want to develop new research at the interface of atmospheric physics and AI. Candidates are encouraged to propose their own PhD project idea within the broad research themes below.
On the atmospheric physics side, topics of interest include, in alphabetical order:
- Aerosol–cloud interactions
- Air–sea and land–atmosphere interactions
- Atmospheric convection and moist turbulence
- Atmospheric predictability and forecasting across timescales
- Atmospheric radiation, including cloud–radiation interactions
- Cloud physics, including microphysical processes
- Post-processing and spatiotemporal downscaling of weather forecasts and climate projections
- Tropical meteorology, including tropical cyclones
- Weather and climate extremes
On the AI side, topics of interest include, in alphabetical order:
- Causal ML, including causal representation learning and causal discovery
- Distillation for scientific discovery, including equation learning
- Generative modeling, including ensemble modeling and uncertainty quantification
- Generalization, including robustness to statistical non-stationarity, for example out-of-distribution climates
- Hybrid physics–AI modeling, including ML parameterizations
- Interpretable ML
- Knowledge-guided ML, including physics-constrained ML
- Responsible use of foundation models for weather and climate applications
- Scale-aware and adaptive AI, including operator learning
- Scientific benchmarks and community evaluation
- Sustainable and resource-efficient AI
The proposal is not expected to be a final PhD plan. Rather, it should help us understand the candidate’s scientific interests and technical capabilities. Promising ideas will be further developed during the selection process and, for the selected candidates, during the PhD. Proposed projects should be creative, feasible, and well aligned with the group’s expertise and collaborative network. Candidates are encouraged to explore our recent publications to identify potential research directions and collaborators: https://wp.unil.ch/dawn/publications/. Both PhD projects may involve collaborations within UNIL, across Switzerland, and internationally, depending on the candidate’s interests and proposed project.
Your responsibilities
The successful candidates will be expected to:
- Conduct independent, innovative, and responsible research at the interface of atmospheric science and artificial intelligence
- Develop a creative and feasible PhD project in collaboration with the supervisor and, when relevant, additional collaborators
- Disseminate research results through peer-reviewed publications, conferences, workshops, and other open-science channels
- Make research outputs as open and reproducible as possible, including code, data-processing workflows, documentation, and preprints where appropriate
- Share progress regularly in group meetings and participate actively in scientific discussions
- Openly discuss research roadblocks, seek advice when needed, and contribute to a supportive lab culture
- Engage with collaborators through regular online and/or in-person meetings, depending on the project
- Contribute to a collaborative, inclusive, and intellectually stimulating research environment
Your qualifications
Applicants should have:
- A master’s degree, or an equivalent degree expected before the start date, in a quantitative field related to atmospheric science, climate science, physics, applied mathematics, statistics, computer science, machine learning, data science, or a closely related discipline
- Strong scientific programming and data-analysis skills, ideally including proficiency in Python
- Experience working with scientific datasets or large-scale numerical model output
- A solid foundation in applied mathematics and/or physics; relevant areas may include calculus, differential equations, statistics, mechanics, thermodynamics, fluid dynamics, numerical modeling, or machine learning
- Strong communication skills in English
- Enthusiasm for both atmospheric science and scientific machine learning
- Willingness to work across disciplinary boundaries and learn unfamiliar concepts when needed
Additional qualifications that are welcome but not required:
- Experience with high-performance computing
- Experience with machine-learning methods or frameworks
- Experience with climate, weather, atmospheric, or environmental datasets
- Experience with numerical weather prediction or Earth-system modeling
- Teaching and/or mentoring experience
- Experience with open-source or reproducible research workflows
Language requirements:
- Position 1: Proficiency in both English and French is required.
- Position 2: Proficiency in English is required. French is not required.
- Proficiency in German is not required for either position. Free French and (Swiss) German courses are available at UNIL.
Application documents
In the interest of fairness to all applicants, incomplete applications will not be considered. Please do not submit a generic cover letter. Instead, applications should include the following documents in PDF format:
- Curriculum vitae
- Copies of all university degree certificates and transcripts
- A separate PDF containing the names, affiliations, and email addresses of two references, for example a master’s thesis advisor, academic staff member who has read your work, or previous employer
- One lead-authored research report, which may be a manuscript, thesis, class paper, technical report, or equivalent written work
- A short additional statement of no more than 250 words addressing:
- your favorite research experience so far and why
- your professional goals, and how this position may help you pursue them
- your teaching and/or mentoring experience; if you have no formal teaching or mentoring experience, describe which teaching or mentoring practices you would like to develop during the PhD
- A personal statement of no more than 500 words, excluding figures and bibliography, describing a creative yet feasible PhD project idea in atmospheric physics and AI. The statement should include:
- a tentative title
- the scientific question you would like to address
- why this question is new, timely, or insufficiently answered in the current research literature
- how the idea connects to one or more topics listed in this job description
- which data and/or models you might use
This proposal is not expected to be final; it is a starting point for discussion and will be refined collaboratively during later stages of the selection process. Generic statements that do not engage specifically with the research themes of the position and the DAWN group are unlikely to be competitive.
What we offer
The positions offer:
- Annual salary ranging from approximately CHF 54k in year 1 to CHF 63k in year 5, contingent on satisfactory yearly reviews
- Funded individual research equipment, including a laptop and related research hardware
- Funding for research-related travel, including conferences, workshops, research visits, and collaborations
- Funding for open-access publication costs when appropriate
- Five weeks of paid holidays per year, in addition to public holidays
- Paid parental leave
- Access to UNIL’s high-performance CPU/GPU computing facilities and in-person computing support
- Opportunities to collaborate within an international research network
- A friendly and cohesive research environment within the Institute of Earth Surface Dynamics
- Participation in group and institute activities, including winter and summer outings
- Access to UNIL campus facilities, including a large sports center and an international campus environment
Additional information
- We are committed to fostering a diverse, equitable, and inclusive research environment. Applications are encouraged from candidates of all backgrounds. The University of Lausanne is committed to equal opportunity and stands firm against all forms of discrimination.
- The Faculty of Geosciences and Environment of the University of Lausanne adheres to the DORA agreement and follows its guidelines in the evaluation of applications: in short, quality over quantity.