57 systems-science "https:" "https:" "https:" "https:" "UCL" "UCL" PhD positions at Forschungszentrum Jülich
Sort by
Refine Your Search
-
least B2 level according to the CEFR: https://go.fzj.de/languagerequirements ); knowledge of German is beneficial Our Offer: We work on the very latest issues that impact our society and are offering you
-
of X-ray methods Knowledge of X-ray optics Knowledge of synchrotron science Knowledge of catalysis and energy storage Experience with programming languages (ideally Python), SPS controls system Fluent in
-
required (at least B2 level according to the CEFR: https://go.fzj.de/languagerequirements ) Our Offer: We work on the very latest issues that impact our society and are offering you the chance to actively
-
which everyone can realize their potential is important to us. The following links provide further information on diversity and equal opportunities: https://go.fzj.de/equality and and on the targeted
-
addition to exciting tasks and the collaborative working atmosphere at Forschungszentrum Jülich, we have a lot more to offer ( https://www.fz-juelich.de/en/careers/julich-as-an-employer/benefits ). The position is for
-
engineering laboratory facility. Your task will include: Construction and commissioning of the new reaction engineering plant Development and synthesis of inductively heatable, heterogeneous catalysts Operating
-
manufacturing in resource strategies and system models for evaluating long-term transformation paths Your Profile: Excellent master`s degree in engineering, materials science, industrial engineering, energy
-
website (pay scale table on page 69 and following of the PDF download): https://go.fzj.de/bmi.tvoed FIXED-TERM: The position is limited to 3 years In addition to exciting tasks and a collegial working
-
electrical or mechanical engineering Strong mathematical skills Experience in modelling energy systems Very good knowledge and experience in programming (e.g. Python, Matlab, C, C++) Fluent in written and
-
, data science, applied mathematics, physics, materials science, or a related field. Solid background in machine learning and/or computer vision. Interest in representation learning, active learning