Doctoral Positions in Exoplanet Atmosphere Characterisation and the Search for Life

We are looking for one or two Doctoral Students to work on the atmospheric characterisation of temperate terrestrial exoplanets and the search for life within the Exoplanets and Habitability Group led by Prof. Sascha P. Quanz at ETH Zurich. The positions is closely connected to the ETH-led LIFE space mission. LIFE is a space-based mid-infrared nulling interferometer to directly detect and spectroscopically characterise dozens of temperate terrestrial exoplanets around nearby stars. The successful candidates will join the LIFE Science Team and work closely with researchers and students at ETH Zurich and across the wider LIFE collaboration.

Project background

A central goal of LIFE is to characterise the atmospheres of temperate terrestrial exoplanets and ultimately assess their habitability and possible signs of life. Understanding which atmospheric properties can be robustly inferred from mid-infrared observations is also essential for translating LIFE's science goals into science requirements and corresponding instrument-performance requirements.

Our group has developed the atmospheric retrieval framework pyRetLIFE and has so far investigated mainly Earth-like planets and classical atmospheric biosignature gases. An important next step is to broaden this work towards the diversity of potentially habitable and inhabited worlds: different atmospheric compositions and climates, non-Earth-like biospheres, non-standard biosignatures, and the abiotic scenarios against which potential signs of life need to be interpreted.

Possible research directions for the successful Doctoral students include

• The modelling and characterisation of non-Earth-like atmospheres and biospheres, using physically motivated atmospheric models and retrievals to understand which properties and potential biosignatures future missions like LIFE can robustly constrain
• The exploration of alternative inference approaches, including machine learning and AI, for atmospheric characterisation and the interpretation of potential signs of life, this could include investigating where such methods provide additional information compared with conventional retrievals, and assessing their robustness, interpretability and sensitivity to modelling assumptions

Job description

• Develop and pursue research on the characterisation of temperate terrestrial exoplanet atmospheres and the search for signs of life in the context of the LIFE mission
• Investigate atmospheric scenarios beyond modern Earth analogues; this may include non-Earth-like biospheres, non-standard biosignatures and/or relevant abiotic alternatives
• Use and further develop atmospheric retrieval and/or complementary modelling and inference approaches
• Explore, where relevant, ML/AI approaches for atmospheric inference and interpretation
• Investigate the robustness and limitations of atmospheric characterisation methods and compare complementary approaches where scientifically useful
• In close collaboration with the LIFE Science Team and LIFE Instrument Science Team, translate atmospheric characterisation results into science requirements and related instrument-performance requirements for LIFE
• Contribute new scientific ideas to the development of the LIFE science case and interact with the broader LIFE collaboration

Profile

• Master's degree (or equivalent degree) in astrophysics, planetary science, atmospheric science, physics or a closely related field, completed by the start date
• Strong interest in exoplanet science, atmospheres, habitability, biosignatures and the search for life
• Experience in one or more of the following is welcome, but not required: atmospheric modelling, atmospheric retrievals, radiative transfer, photochemical or climate modelling, statistical inference, machine-learning/AI methods, or related numerical approaches
• Strong scientific programming skills, preferably in Python; experience with AI and machine learning tools is an asset
• Ability and interest to work in a team and across disciplinary boundaries
• Ability to interact with the broader exoplanet, atmospheric science and astrobiology communities
• Scientific curiosity, independence and a collaborative approach to research
• Very good command of English (spoken and written)

We offer

• A collaborative and interdisciplinary research environment within the Exoplanets and Habitability Group and the LIFE Space Mission team at ETH Zurich, with close links to the international LIFE collaboration
• A fully funded four-year Doctoral Position with competitive salary and benefits according to ETH regulations, including support for conference travel, computing and career development

We value diversity and sustainability

In line with our values, ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our Equal Opportunities and Diversity website to find out how we ensure a fair and open environment that allows everyone to grow and flourish. Sustainability is a core value for us – we are consistently working towards a climate-neutral future.

Curious? So are we.

We look forward to receiving your online application with the following documents:

• CV
• University transcripts and, if already available, diploma
• A statement of research interests (max. 2 pages), indicating which of the research directions described above you would be particularly interested in pursuing.
• Names and contact details of three referees

The application deadline is November 25, 2026. The start date is flexible, but we envision to start in spring / early summer 2027.

Further information about the group can be found on our website. Questions regarding the position and informal enquiries are welcome and should be directed to Prof. Sascha P. Quanz, sascha.quanz@phys.ethz.ch. Please note that applications must be submitted exclusively through our online application portal; applications sent by email or post will not be considered.

We would like to point out that the pre-selection is carried out by the responsible recruiters and not by artificial intelligence.