160 coding-"https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" positions at Forschungszentrum Jülich
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
mentoring for building a career in academia or industry Professional development through JuDocS, including training courses, networking, and structured continuing education ( https://www.fz-juelich.de/en
-
development is important to us – we support you specifically and individually e.g., through training and networking opportunities specifically for doctoral candidates (JuDocS): https://go.fzj.de/JuDocs FAIR
-
opportunities specifically for doctoral candidates (JuDocS): https://go.fzj.de/JuDocs HEALTH & WELL-BEING: Your health is important to us. You can look forward to a comprehensive company health management
-
FLEXIBILITY: Flexible working time models, including options close to full-time ( https://go.fzj.de/near-full-time ), allow you to tailor your working hours to suit your individual needs FAIR REMUNERATION
-
individually e.g., through training and networking opportunities specifically for doctoral candidates (JuDocS): https://go.fzj.de/JuDocs SUPPORT FOR INTERNATIONAL EMPLOYEES: Our International Advisory Service
-
, please have a look at our institute website: https://www.fz-juelich.de/en/pgi/pgi-7 and the research group in which this position is located: https://www.fz-juelich.de/en/pgi/pgi-7/research-groups-1/ag
-
structured training for your tasks. We also support you from the very beginning and make your start easier with our Welcome Days and Welcome Guide: https://go.fzj.de/welcome WORK-LIFE BALANCE: We offer
-
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 Days and Welcome Guide: https
-
energy system models based on the institute`s own open-source FINE framework https://github.com/FZJ-IEK3-VSA/FINE. Your tasks in detail: Implementing geothermal plants with material co-production in
-
Your Job: This PhD project bridges between classical analytical methods and modern AI based techniques to analyse spike train recordings to advance our understanding of neural population coding