The University of Bonn is an internationally operating research university with a broad spectrum of subjects. With 200 years of history, around 38,000 students, more than 6,000 employees and an excellent reputation: The University of Bonn is one of the most important universities in Germany. In the recent excellence initiative, the University of Bonn was the most successful university in Germany with six Clusters of Excellence.
In this excellent scientific environment, the Interdisciplinary Research Unit Mathematics and Life Sciences (https://www.mathematics-and-life-sciences.uni-bonn.de/en) develops and applies novel mathematical approaches and software tools for data analysis and modelling. Application areas include cancer and immunology, with an emphasis on high-throughput (single-cell) data. We are intensively collaborating with world leading experts in mathematics and immunology in the Hausdorff Center for Mathematics, ImmunoSensation2, and the German Center for Neurodegenerative Diseases. Currently, we are searching for individuals who strengthen our team.
Project description:
Most biological tissues consist of many different cell types and are highly organized. The corresponding spatio-temporal patterns are relevant in many biological and biomedical processes including tissue homeostasis, viral infection or tumor development, and can be studied with imaging techniques, such as light and fluorescence microscopy. Biomedical imaging data provides quantitative information about biological systems, however, mechanisms causing spatial patterning and causalities often remain elusive. To close this gap, multi-scale computational modelling can be employed.
The goal of this project is to develop a computational pipeline for the analysis of tissue dynamics. The research project with focus on model development and parameterization. The project is part of the collaborative research project FitMultiCell in which a novel pipeline for the model-based analysis of imaging data is to be established. The methods are based on some of our recent work on multi-scale modelling (Jagielle et al., Cell Systems, 2017; Klinger et al., Bioinformatics, 2018). Applications will focus on the modelling of virus transmission modes in biological tissues. Knowledge about transmission modes will facilitate the design of more effective anti-viral treatments.
Job description:
- Development of multi-cellular models (e.g., virus transmission)
- Development of scalable parameter estimation methods for multi-cellular models
- Implementation of methods for high-performance computing (HPC) infrastructures
- Application of methods and interpretation of the results
- Collaboration with national and international partners
Your profile:
- Master degree in computer science, engineering, mathematics, physics or equivalent
- Background in computational modeling, statistical inference or machine learning
- Programming experience (preferably Python and/or C++)
- Background in HPC
- Proficiency in written and spoken English
- Passion for science and scientific work
Our offer:
- Working in an innovative, well-equipped and scientifically stimulating environment
- Further training opportunities
- Initial short-term employment contract for 3 years with a standard public service salary (TV-L EG 13, 75%)
The University of Bonn is committed to diversity and equal opportunity. It is certified as a family friendly university. It aims to increase the proportion of women in areas where women are under-represented and to promote their careers in particular. It therefore urges women with relevant qualifications to apply. Applications will be handled in accordance with the Landesgleichstellungsgesetz (State Equality Act). Applications from suitable individuals with a certified serious disability and those of equal status are particularly welcome.
The deadline for the application round is October 31, 2019. Application documents (cover letter, CV, certificates, and two reference letters or contact details of former advisors) should be submitted as soon as possible as a single PDF file via email.
Contact: Prof. Dr. Jan Hasenauer, jan.hasenauer@uni-bonn.de
