Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- DAAD
- Technical University of Munich
- Fraunhofer-Gesellschaft
- Nature Careers
- Humboldt-Stiftung Foundation
- Leibniz
- Forschungszentrum Jülich
- Hannover Medical School •
- Heidelberg University
- Helmholtz-Zentrum Geesthacht
- Ludwig-Maximilians-Universität München •
- Max Planck Institute for Biogeochemistry, Jena
- Max Planck Institute for Human Cognitive and Brain Sciences •
- Max Planck Institute for Sustainable Materials •
- University of Bremen •
- University of Münster •
- University of Tübingen
- 7 more »
- « less
-
Field
-
the testing of newly devel-oped materials and the use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission
-
and machine learning to establish a modeling framework that uses omic data for providing effective degradation rates of biomolecules and predictions of their impact on soil organic matter turnover
-
, and therapy resistance mechanisms Ability to work independently and collaboratively within interdisciplinary teams Prior experience with network modeling or machine learning is a plus We offer
-
learning and data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms
-
civil/electrical/control engineering or mathematics or related study programs with a solid basis in choice modelling and/or reinforcement learning, with knowledge of MATSim is advantageous. Description
-
, C/C++ and/or Java, etc.; experience with the implementation of specialized transport modelling software, optimization algorithms and procedures; strong ability and desire to learn new programming
-
Dortmund, we invite applications for a PhD Candidate (m/f/d): Analysis of Microscopic BIOMedical Images (AMBIOM) You will be responsible for Developing new machine learning algorithms for microscopy image
-
. Specifically, the PhD candidate is expected to contribute corpora preparation (collection and organizing the annotation), use machine learning approaches for irony detection, and testing for experimental and
-
– from the modeling of material behavior to the development of the material to the finished component. PhD Position in Machine Learning and Computer Simulation Reference code: 50145735_2 – 2025/WD 1
-
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