Sort by
Refine Your Search
-
), biostatistics, machine learning, data science and research data management, and causal inference methods (Iris Pigeot, Marvin Wright, Vanessa Didelez), and etiologic and molecular epidemiology (Konrad Stopsack
-
Leibniz Institute of Plant Biochemistry (IPB) in Halle (Saale), Germany, where we are offering a fully-funded PhD position within the DFG Priority Programme SPP2363: “Molecular Machine Learning”. About the
-
developing a digital twin, employing machine learning and numerical computations of atomistic processes. At IKZ, a kinetic Monte Carlo tool has been developed in the programming language julia. This allows a
-
. The candidate will also collaborate with the Department of Computer Science at Kiel University and the remote sensing company EOMAP GmbH, employing state-of-the-art machine learning techniques to improve
-
Computer-adaptive methods and multi-stage testing Application of machine learning in psychometrics Predictive modeling of educational data Methodological challenges in cohort comparisons Advanced meta
-
as a PhD student in TUM’s graduate programme. Key responsibilities: Co-designing research methodology/approaches to study the political economy of climate mitigation policies in low- and middle-income
-
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
-
after a positive evaluation is possible and aspired. Your responsibilities We are looking for a motivated researcher who is passionate about data and shares the RDC’s vision of making complex microdata
-
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
-
the programme area ‘Plant Adaptation’ (ADAPT). The aim of the research project is to understand how intrinsically disordered regions (IDRs) and prion-like domains (PLDs) control the temperature responsiveness