-
following position Postdoctoral researcher (m/f/d) in Environmental Data Science and Machine Learning for the project BoTiKI Location: Görlitz Employment scope: full-time (40 weekly working hours) / part
-
The Network Analysis and Modelling group investigates how genetic variation shapes gene regulation, protein function, and, ultimately, observable plant traits. Using machine learning and network
-
. The Leibniz Institute for Neurobiology (LIN) is an internationally recognized neuroscientific research institute and dedicated to the research on learning and memory. Our research comprises all organizational
-
in machine learning, AI and programming skills, e.g. Python basic knowledge of materials science / materials engineering Leibniz-IWT is a certified family-friendly research institute and actively
-
reduction, uncertainty quantification, machine learning, fluid mechanics. Experience with scientific object-oriented programming languages (C++, Python, or Julia) is highly relevant. Knowledge
-
timings) affect the metabolome and proteome of rapeseed seeds. Your findings will serve as molecular fingerprints to support Deep Learning models for hybrid development. Whom we are looking for: An early
-
or a related discipline A solid background in climate and atmospheric sciences, and extreme weather ideally supported by knowledge of machine learning and time series analysis is of advantage, as is
-
that enables you to successfully negotiate with partners and institutions is a requirement You are a team player and like to take responsibility for yourself and others. You enjoy learning from and
-
committees is English; Very good spoken and written command of English, willingness to learn German during the duration of the employment. You can expect: A motivated, multi-cultural team of international
-
or Python Machine learning methods (for the baseline prediction for the reward funds) is beneficial We expect: Strong motivation to contribute to policy-relevant research Strong interest in teamwork and