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English PhD Research Fellow in Deep learning for imaging Apply for this job See advertisement About the position Position as PhD Research Fellow in machine learning available at Department for Informatics
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both on the sequence and structural level, developing and employing machine-learning tools for predicting antibody-epitope binding. In silico antibody design is a long-standing computational and
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on how collaborative practices evolve with these powerful tools, and support learning in disciplinary or interdisciplinary contexts. In addition, the nature of the interaction between human and machine
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SUMOylation, transcription factors, or chromatin dynamics. Expertise in machine learning or statistical modeling for biological data. Knowledge of enhancer-promoter interactions and 3D genome organization. All
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SUMOylation, transcription factors, or chromatin dynamics. Expertise in machine learning or statistical modeling for biological data. Knowledge of enhancer-promoter interactions and 3D genome organization. All
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for Knowledge-driven Machine Learning. We are looking for a motivated researcher, who has experience with both theoretical, methodological and applied research in change and anomaly detection in sequential data
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such as R, Python, Julia, etc. Familiarity with AI algorithms and Machine Learning Fluent oral and written communication skills in English Desired qualifications: Experience with research on epidemiological
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power electronics Machine learning Renewable energy systems Advanced statistics Language requirement: Good oral and written communication skills in English English requirements for applicants from outside
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. Desired: Familiarity with statistical and machine learning techniques. Knowledge about molecular biology and/or gene regulation. Experience with nanopore sequencing, Hi-C, ribosome profiling, or CAGE data
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or more of the following empirical research methods will be considered an advantage: applied microeconometrics and causal inference; machine learning and data science. Experience with one or more of the