Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- CNRS
- University of Oslo
- Uppsala universitet
- NTNU - Norwegian University of Science and Technology
- Radboud University
- University of Southern Denmark
- Aalborg University
- Christian-Albrechts-Universitaet zu Kiel
- Ecole Centrale de Lyon
- Faculty of Science University of Zagreb
- Forschungszentrum Jülich
- Fritz Haber Institute of the Max Planck Society, Berlin
- Humboldt Universität zu Berlin / Leibniz Universität Hannover
- Integreat -Norwegian Centre for Knowledge-driven Machine Learning
- KU LEUVEN
- Leibniz University Hannover
- Max Planck Institute for Mathematics •
- NTNU Norwegian University of Science and Technology
- Newcastle University;
- Ruhr-Universität Bochum •
- Technical University of Denmark
- Technische Universität Berlin •
- The University of Chicago
- The University of Manchester
- Umeå University
- University of Bonn •
- University of Newcastle
- Université Toulouse Capitole
- Utrecht University
- Vrije Universiteit Amsterdam (VU)
- 20 more »
- « less
-
Field
-
The Master project should treat methodological aspects with mathematical tools. The candidate must show a strong interest in method development. Proven competence in probability, linear algebra, and
-
subsystem characterizations to take into account similarities (e.g. algebraic or topological) in their modeling. The goal is to improve the trade-off between algorithmic complexity and conservatism by finding
-
. The candidate must show a strong interest in method development. Proven competence in probability, linear algebra, and statistical modelling are essential for this position. Demonstrated strong proficiency in
-
for integrating, combining and representing data from heterogeneous sources (satellite imagery, plant monitoring, management…). New algebraic operators adapted to AI requirements needed for the development
-
into the following sections: A - Algebra, Number Theory and Logic B - Analysis and Differential Equations C - Discrete Mathematics D - Geometry and Topology E - Numerical Mathematics and Scientific Computing F
-
/ TensorFlow / Scikit Learn Highly knowledgeable in mathematical and statistical concepts Solid foundation in mathematics for Machine Learning (Linear Algebra, Probability, Optimization). Proficient in English
-
work on the following project: PK.1.1.10.0004 - Implementation of top research within the Scientific Center of Excellence for Quantum and Complex Systems, and Representations of Lie Algebras, for a fixed
-
joint doctoral programme of the three Berlin universities and the graduate school of the Cluster of Excellence MATH+. Areas of expertise include: Geometry and topology Algebraic geometry and number theory
-
we favor candidates with previous experience in X-ray imaging preferably for biomedical applications. You should Have a solid grasp of microscopy, electromagnetism/optics and linear algebra Be skilled
-
members and more than 55 doctoral students and postdoctoral fellows. The Department conducts research at an international high level within the disciplines of algebra, analysis, didactics of mathematics