53 phd-in-mathematical-modelling-population Postdoctoral positions at Technical University of Munich
Sort by
Refine Your Search
-
communication system are modeled using information theory. We wish to investigate how interleaving can reduce the overhead and computational load due to coding coefficients required in classical linear random
-
(with experiments in the field and in the lab) and modelling techniques. The focus of this postdoctoral position is the generation of empirical datasets for livestock systems in East Africa, and in
-
good publication track record Above-average master’s degree in computer science, electrical/ mechanical engineering, applied mathematics, or a similar engineering-oriented quantitative discipline
-
competitive dynamics between cell nuclei and how their interaction leads to emergent organism-scale behaviour. You will perform fluorescence microscopy on nuclei populations and quantify their dynamics while
-
will develop into acute or chronic infection. Your expertise - PhD in life sciences, preferably (liver) immunology and/or viral hepatitis. - Experience in high-dimensional flow cytometry for phenotyping
-
cooperation with the other scientists is a prerequisite. Your profile: You have a PhD, work experience and several publications in the field of solid oxide cells. In addition, fluent written and spoken English
-
on the nanoscale (previous works e.g.: https://www.nature.com/articles/s41563-019-0555-5). You will also supervise one PhD student who will work on a complementary topic guaranteeing quick output and an ideal
-
to 5 and more years. Requirements: • You have a PhD degree (or postgraduate degree MSc) in a computational discipline, preferably with significant experience in Bioinformatics or Computational Biology
-
preliminary work! • You will characterize metalloid transport proteins. • You will be involved in the training of students on the Bachelor and Master level. YOUR QUALIFICATIONS AND SKILLS • You have a PhD or
-
consortium-based tasks related to the 6G-Life project. Additionally, the methods and findings developed throughout the PhD track will be scalable and applicable to other research projects in MIRMI