J. Wolf Lab

If you are interested in joining our lab, please contact our us at office.wolf@mdc-berlin.de and include the following documents in your application: CV, relevant certificates/ university transcripts (listing the courses and grades), a short text describing why you are interested in joining our lab (email text is fine), when you would like to start (for interns: how long you would like to join us).

Possible Research Project

Please send your application to office.wolf@mdc-berlin.de.

Spatial aspect of the inter cellular communication of muscle stem cells

Student project

Cells in tissue communicate with each other through a variety of methods, in order to maintain tissue integrity or to respond to tissue external queues. One, well studied, way of cell-to-cell communication is the Delta Notch signaling pathway, in which the membrane embedded Notch receptor recognizes the Delta ligand on the surface presented by the neighboring cell. Muscle stem cells MSCs use the Delta-Notch-Signaling pathway to communicate, in particular to transduce information of the cell state. After an injury or during muscle development the muscle stem cells have to proliferate, i.e. to increase in numbers, as well as to differentiate and eventually form new myofibers.

In your study you will help to understand how the cell-to-cell communication helps the muscles to respond to an injury an orchestrate the and balance the differentiation and renewal of MsCs. 

Building on an existing computational model created with the Morpheus, you will test the impact of the spatial arrangement as well as of crucial parameter on the multicellular communication. And if needed improve the mathematical model.

Requirements

• Background in computational biology, bioinformatics, biophysics, or a related field.
• Strong programming skills in Python (NumPy, SciPy, Matplotlib, etc.).
• Basic knowledge of systems biology, cell signaling, or developmental biology.
• Experience with mathematical modeling and/or Morpheus (or willingness to learn).
• Curiosity for mathematical models of biological processes

Project Details

• Level: Suitable for advanced Bachelor’s or Master’s students
• Duration: 8–12 weeks, flexible part-time commitment
• Start Date: Flexible (e.g., upcoming term or semester)
• Compensation: Unpaid; can be credited as a thesis, seminar project, or academic credit

Download project description (PDF)

Developing a Simulator for Temporal scRNAseq Data

Student project

Analyzing temporal single-cell RNA sequencing (scRNA-seq) data requires new computational methods—and reliable ground truth datasets to test them. Since such data are often unavailable or infeasible to collect experimentally, simulation becomes essential.

In this project, you will contribute to the development of a Python-based simulation tool that generates temporal scRNA-seq data. The model uses an agent-based framework to represent cell proliferation and death, combined with Langevin dynamics to simulate differentiation as movement in a transcriptomic potential landscape. This approach enables the creation of complex, realistic datasets for testing new analysis pipelines.

You will help to implement and refine the core simulation logic in Python. Furthermore you will help to improve performance and flexibility of the tool itself as well as the downstream analysis. The goal is to create ready-to-use Python package including documentation and version control (GitLab).

Requirements

• Solid programming skills in Python
• Interest in computational biology, agent-based modeling, or systems biology
• Familiarity with stochastic processes, Langevin dynamics, or single-cell biology is a plus
• Experience with Git/GitLab and writing clean, modular code is welcome

Details

• Duration: ~8–12 weeks (flexible)
• Level: Advanced Bachelor’s or Master’s project
• Compensation: Unpaid; suitable for thesis or academic credit

Download project description (PDF)