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for the physical sciences. We have a strong profile in computational statistics, simulation and learning algorithms, and scientific software development. As a closely collaborating, international team
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The Data Integration in the Life Sciences group, led by Prof. Dr. Katharina Baum, is seeking a motivated student assistant to contribute to the cutting-edge, BMBF-funded research project Act-i-ML
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, execution and analysis of three cooperative sub-projects within the FADOS network: The development of kinetic Monte-Carlo algorithms with realistic working parameters which account for inhomogeneous and
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and development in designing and programming fied programmable gate arrays (FPGAs) for accelerating artificial intelligence (AI) algorithms. contributing, administrating and reporting in (inter
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We are the research groups “Tectonics and Sedimentary Systems” of the Institute of Geological Sciences at the Freie Universität Berlin under the direction of Prof. Dr. Alexander Webb and Prof. Dr
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multi-parameter ion-beam tuning procedures (collaboration with Univ. of Vienna and HZDR) and developments of machine learning (ML)-algorithms for optimization of beam parameters and control of relevant
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of terrestrial systems analysis, we seek a candidate who can develop and lead future research activities in one or more of the following directions or related topics: Innovative observation methods for terrestrial
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developing a machine learning (ML) algorithm for the automated analysis of the above-mentioned mass spectra. Desirable: - knowledge in the field of Planetary Sciences - very good written and spoken English (C1
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difference. Make something out of it! In our video you will find information about our student assistants and their work. What you will do Driving innovative AI research through the development and
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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