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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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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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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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implementation, practical application, theoretical analysis and evaluation of AI algorithms Use of XAI tools to explain machine learning models Implementation of deep learning Improvement of models, e.g. in terms
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RWTH Aachen University, Department of Mathematics Position ID: RWTH -PROF [#26602, BANF 29059] Position Title: Position Location: Aachen, Northrhine-Westphalia 52056, Germany [map ] Appl Deadline
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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
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software frameworks Development of new signal processing algorithms (PHY/MAC) in conjunction with software-defined radio hardware Development and validation of AI/ML methods for mobile communications systems
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of multi-omics data sets generated with innovative high-throughput technologies used in Research Sections I and II (e.g. sensory, metabolome, proteome, and transcriptome data) by using efficient algorithms
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-omics data sets generated with innovative high-throughput technologies used in Research Sections I and II (e.g. sensory, metabolome, proteome and transcriptome data) by using efficient algorithms and
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efficient algorithms and machine learning/artificial intelligence methods in combination with complex network analysis tools to predict and model interactions between food and biological systems • Further