In January 2027, I will start the Lange Lab at the Department of Biomedicine (DBM) and the Basel Research Centre for Child Health (BRCCH) of the University of Basel ๐จ๐ญ๐๏ธ, as Tenure-Track Assistant Professor in Systems Developmental Medicine.
We will build computational methods to understand how human tissues and organs mature, from early development through childhood. That means integrating single-cell, spatial, and imaging data into models that describe what healthy maturation looks like โ and that can flag where a tissue departs from it.
Methodologically, we sit close to the current frontier of generative modeling: flow matching and diffusion models, variational autoencoders, Wasserstein gradient flows and optimal transport, vision transformers and other large-scale representation learners. Biologically, we work with organoid model systems and primary human tissue ๐ง . We’re interested in developing computational methods that study regulation across molecular layers, cell-state dynamics, and communication patterns, and we apply these to biological settings with a focus on early human development.
I am recruiting now for positions starting in 2027. Applications are considered on a rolling basis, and there is no deadline.
PhD students ๐#
You would develop a computational method and drive it through to a biological result โ designing the model, implementing it, and interpreting what it says about a real developmental system. Doctoral positions in Basel are fully funded and typically run four years. You will be embedded in the DBM and BRCCH environment, with close access to clinicians and to primary pediatric samples.
Please apply via Uni Basel’s online portal
Postdocs ๐ฌ#
You would take on a substantial, largely self-directed project, and I expect you to shape its direction. There is room to build tools that outlive the project, and to work directly with the clinical side of the BRCCH network.
If you are considering a fellowship (EMBO, HFSP, Marie Skลodowska-Curie, SNSF, and others), please get in touch early โ I am glad to co-develop the proposal with you, and this is a good route into the lab.
Please apply by emailing marius.lange@unibas.ch with:
- your CV,
- a link to your GitHub profile,
- a short paragraph on your research interests and why this lab in particular,
- contact details for two referees.
MSc thesis projects ๐#
I supervise Master’s theses of at least six months.
Projects run in two directions. The first continues my current work: cellular representations and cellโcell communication in spatial genomics data, with a focus on organoids and early human brain development. The second grows with the lab โ primary pediatric samples and questions in child health, with clinical collaborators close by. Both mix data analysis, mathematical modeling, machine learning, and biological interpretation โ and sometimes discovery ๐.
Please apply by emailing marius.lange@unibas.ch with:
- your CV,
- a link to your GitHub profile,
- a short paragraph on your research interests and why this lab in particular,
What I look for#
Less about how much code you can produce โ models and tooling handle a growing share of that โ and more about judgment:
- Theoretical grip on the models you use. You can say what a model assumes, where those assumptions break, and why the result is or isn’t trustworthy. Being able to call a method is not the same as understanding it.
- Biological understanding, or a serious appetite for it, particularly in development and regeneration. You should want to know what the answer means, not just whether the loss went down.
- Practical research experience. Evidence that you have carried a project through messy, real data to a conclusion โ a thesis, a paper, a preprint, a tool people use.
- Fluency in the modern stack. You should be genuinely productive in JAX or PyTorch โ of everything on this list, that is the one I would find hardest to work around. Knowing your way around the surrounding ecosystem is a real plus: Hugging Face, Optuna, Weights & Biases, and the scverse tools.
Python is our working language and you should be comfortable in it, but treat that as the floor rather than the qualification. Backgrounds vary: physics, mathematics, computer science, statistics, bioinformatics, and computational or systems biology all work. You do not need to arrive with all of the above โ strong ML/AI people with some exposure to biology or single-cell data are exactly who I hope to hear from, and biologists with genuine quantitative depth are equally welcome.