64 structures "https:" "https:" "https:" "https:" "https:" "https:" "https:" "https:" "https:" scholarships at Forschungszentrum Jülich
Sort by
Refine Your Search
-
): https://go.fzj.de/bmi.tvoed PERSPECTIVE: The position is initially for a fixed term of 3 years but with the prospect of longer-term employment SUPPORT FOR INTERNATIONAL EMPLOYEES: Our International
-
population-level neural interactions. Prior work has emphasized rate-based codes due to their relative simplicity; our approach will explicitly extend these models to capture temporal structure within spike
-
on the campus of Forschungszentrum Jülich. Your tasks include in detail: Construction and commissioning of a new test stand for the investigation of the continuous butanediol dehydrogenation under dynamic
-
development, stack construction, system and component development, microscopy, spectroscopy) Presentation of findings at specialist conferences, publication in leading journals and active exchange with industry
-
) conferences Unique HDS-LEE graduate school program (including data science courses, soft skill courses and annual retreats) https://www.hds-lee.de/about/ Qualification that is highly welcome in industry Further
-
: It is important to us that you quickly settle into the team and are given structured training for your tasks. We also support you from the very beginning and make your start easier with our Welcome
-
information about our institute here: https://www.fz-juelich.de/en/ias/ias-8 Your Job: Develop physics-aware simulations of growing cell populations, including their spatiotemporal manipulation in microfluidic
-
data science courses, soft skill courses and annual retreats) https://www.hds-lee.de/about/ 30 days of annual leave (depending on agreed working time arrangements) and provision for days off between
-
Your Job: In the CrowdING project, you will analyze experimental data from large crowds and develop quantitative measures to describe their spatial structure. To do this, you will use and expand
-
explicitly extend these models to capture temporal structure within spike trains thereby moving towards analyses that are sensitive not just to firing rates but also precise timing relationships underpinning