PhD position in Mathematical/ Computational Immunology (m/f/d)

at  Universittsklinikum Erlangen

State-of-the-art medicine and nursing care you can rely on! - Since being founded in 1815, Universitätsklinikum Erlangen has offered medicine of the highest standard and incorporated the latest insights from medical research and state-of-the-art equipment into diagnosis and therapy. More than 9.800 employees from approximately 50 different occupations are needed to provide the wide range of services offered by Universitätsklinikum Erlangen, ensuring our patients receive the very best care around the clock.

ESSENTIAL EXPERIENCE/ QUALIFICATIONS:

Applicants should hold a MSc degree in mathematics, (bio-) physics, computational biology, data science or other relevant disciplines
Strong quantitative and mathematical background is required
High motivation and ability for interdisciplinary and collaborative work, ability to work at the interface of the life sciences and data analytical methods
Good programming skills in R, Python and/or C++
Proficiency in English

The GrawLab within the Department of Medicine 5 works on the modelling and analysis of immune processes in the context of inflammation, infection and cancer. By combining various experimental and clinical data with mathematical models and data analytical methods, we aim at a mechanistic and quantitative understanding of the processes that regulate immune responses and determine disease outcome and therapy.
We have an open PhD position (m/f/d) in the field of Mathematical Modelling and Computational Immunology. We are looking for a highly motivated candidate to work at the interface of mathematics/data analysis and the life sciences. You will work on the development of novel mathematical and data analytical methods to analyze multi-scale and high-dimensional experimental and clinical data. The work will especially focus on lymphocyte turnover and migration dynamics considering individual cell-based measurements. Methods involve concepts from machine learning, complex dynamical systems, high-dimensional data analysis and probability/statistics. The candidate should have a strong background in mathematics or physics. The work is embedded within a stimulating research environment involving the interaction with partners from machine learning, data analysis and modelling, as well as experimental and clinical collaboration partners.