Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
, 100% funded PhD student position to fill starting around June 2026. Research is to be in the field of computational methods in nonlinear and large scale optimization / inverse problems or in novel
-
Analysis of Electronic Structure Methods for Molecules and Materials. About the PhD Project: The goal of the project is the development of a posteriori error estimates for state-of-the-art numerical methods
-
to select, adapt, and apply design methods to open research and design questions Application of speculative design methods — futuring, design fiction, scenario building Facilitation & teaching — designing and
-
26.03.2026, Academic staff Doctoral Candidate f/m/d in computational proteomics/bioinformatics with a focus on plant proteomics Candidates must hold a master´s degree in Data Engineering, Data
-
for magnetic particle transport in fluid flows and validating the results through a laboratory-scale reactor. It combines numerical modeling, AI methods, and hands-on experimental work in the context of advanced
-
Informatics Initiative (MII)/FHIR standards Design and implement methodological concepts and software for benchmarking frameworks for AI evaluation Independently develop and implement research ideas within
-
University of São Paulo, Brazil. This position focuses on developing advanced computer vision methods and hardware setup for detecting and predicting plant diseases in soybean cultivation. About Us The Chair
-
theoretical and computational methods to describe electronic, optical, and transport properties of complex materials. The first advertised project (a) is dedicated to the methodological enhancement
-
07.08.2025, Academic staff The Chair of Computational Mathematics at the Technical University of Munich (TUM) invites applications for one PhD position. The Chair of Computational Mathematics
-
Processes (MDPs) and stochastic dynamic programming Risk-sensitive and robust optimization Learning-based approaches (e.g., reinforcement learning, inverse learning) Numerical validation using real-world