Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- Fraunhofer-Gesellschaft
- Technical University of Munich
- Forschungszentrum Jülich
- Nature Careers
- DAAD
- Leibniz
- Free University of Berlin
- Max Planck Institute for Brain Research, Frankfurt am Main
- ;
- Deutsches Elektronen-Synchrotron DESY •
- Fritz Haber Institute of the Max Planck Society, Berlin
- Helmholtz-Zentrum Geesthacht
- Max Planck Institute for Molecular Genetics •
- Max Planck Institute for Multidisciplinary Sciences, Göttingen
- Max Planck Institute for the Structure and Dynamics of Matter, Hamburg
- Max Planck Institutes
- RWTH Aachen University
- Saarland University •
- Technische Universität München
- University of Bremen •
- University of Potsdam •
- University of Tübingen
- 12 more »
- « less
-
Field
-
Group (EASE IRTG), Empowering Digital Media (EDM), the Research Training Group HEARAZ , the Research Training Group KD²School (KD²School), π³: Parameter Identification – Analysis, Algorithms
-
molecular biology techniques as well as in algorithms, statistics and artificial intelligence for molecular genetics. Importantly, mastery of the experimental and theoretical aspects shall equip doctoral
-
processing, algorithm design, optimisation and simulation, software engineering and automation and control systems. An overview of the current PhD research projects is given here: https://www.dashh.org
-
students who would like to write their final thesis in the field of machine learning / computer vision. The primary goal of this master’s thesis is to develop an algorithm that can accurately and efficiently
-
research studies for automated image analysis. In particular, you will: Plan, develop, and implement AI/ML algorithms for pathology image analysis. Integrate multi-modal data (e.g., genomics, clinical data
-
Your Job: Developing and implementing QC algorithms (QAA, QAOA, QSVM), quantum AI algorithms, use case adapted algorithms to test and benchmark latest technology focusing on gate-based QC Advancing
-
data analysis and develop sophisticated mathematical models for simulating power system behaviors under various scenarios. Development and Testing: Design and develop control algorithms to enhance grid
-
, machine learning algorithms, and prototypical energy management systems (EMS) controlling complex energy systems like buildings, electricity distribution grids and thermal energy systems for a sustainable
-
problems Evaluation and advancement of methods for the robustness certification of neural networks with deterministic or stochastic methods Adaptation of near-team and fault-tolerant algorithms for quantum
-
their reliability and resource efficiency during production and operation. The »KI-unterstütze Simulation« team combines physically based simulation approaches with efficient and advanced mathematical algorithms and