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macromolecular dynamics with statistical mechanics, molecular simulation at different resolutions, machine learning, and experimental data. Our group works on the definition and implementation of strategies
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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
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interdisciplinary cooperation as well as cooperation with existing research groups in mathematical physics, dynamical systems, data science, machine learning, control theory, optimisation, or numerics are expected
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federated learning for decentralized AI model training for quality assurance of machining processes within the project »FL.IN.NRW «. A custom dataset composed of machine internal signals and external sensor
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looking for PhD Students in areas related to: Cybersecurity, Privacy and Cryptography Machine Learning and Data Science Efficient Algorithms and Foundations of Theoretical Computer Science Software
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). Knowledge of Docker and machine learning is considered a plus. Knowledge of standard bioinformatics tools for analyzing and interpreting Next Generation Sequencing data. Excellent oral and written
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, memristive devices), and the evaluation with e.g. machine learning and image processing benchmarks Requirements: excellent university degree (master or comparable) in computer engineering or electrical
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looking for PhD Students in areas related to: Cybersecurity, Privacy and Cryptography Machine Learning and Data Science Efficient Algorithms and Foundations of Theoretical Computer Science Software
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cutting-edge big/deep data analysis methods, including machine learning and artificial intelligence. The ideal candidate will therefore have a strong background in data science and in the application and
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of these patients. The goal of this project is to combine cutting-edge multi-omics technology, data analytics, machine learning and clinical samples from the human eye to decipher new insights into disease mechanisms