AI in Computational Biology with a focus on mechanistic learning for multicellular systemsFull PhD

DAAD, Germany

Updated: 3 months ago

Description

Where: At the Chair for Computational and Theoretical Biology ( CCTB ) and the Center for Artificial Intelligence and Data Science ( CAIDAS ) of the University of Würzburg.

Project description: Spatial interactions are key processes for the development and maintenance of multicellular systems. Disturbances in interactions lead to developmental disorders or diseases. In many cases, the details of the process are not yet fully understood. Mechanistic learning, the combination of mathematical mechanistic modelling and machine learning, enables a data-driven investigation of the processes underlying spatial interactions. The aim of this project is to establish machine learning methods for multicellular systems and then combine them with an existing mechanistic model of our research group. The project involves close collaboration with experimentalists who provide the relevant data. Machine learning methods will be applied to link experimental (imaging) data to a mechanistic model. The results of the project will advance our understanding of the general principles of spatial interactions in multicellular systems. In addition, new hypotheses will be generated that can then be tested experimentally. 

Qualifications:

 • Completed academic university degree (Master level) in mathematics, computer sciences, physics or a related discipline 

• Knowledge of programming, machine learning methods, mechanistic modelling and image analysis 

• Good English language skills (spoken and written) 

• Ideally, prior publications 

• Ideally, prior knowledge of biology

 • Enthusiasm for communication with experts from other disciplines is essential 

• Interest in teaching courses 

We are looking for a highly motivated candidate who is team-oriented and willing to learn and work independently and precisely. 

We offer a friendly working environment, excellent computing infrastructure, and supportive supervision.


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