65 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Univ" "Univ" scholarships at Nature Careers
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of novel probabilistic deep-learning models that automatically extract mechanistic and statistical knowledge from your in vivo perturbational omics data. This interdisciplinary atmosphere has been a main
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of young scientists (Master / PhD / Postdoc). Our expertise lies in quantum foundations, quantum information theory and quantum technologies. For additional information, please visit: https
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therapeutics. For more details see this review: https://doi.org/10.1016/j.trecan.2022.09.001 Please get in touch if you don’t have access to the review. The candidate will: Perform Oxford Nanopore sequencing
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programme at the Faculty of Science . The ideal candidate has a background in or experience with one or more of the following topics: Advanced deep learning architectures Mathematical foundations of machine
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of artificial intelligence, machine learning and/or deep learning experience in scientific publishing and presenting research results knowledge or experience in public health research Personal skills Independence
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The Section of Bioinformatics, DTU Health Tech is world leading within Immunoinformatics and Machine-Learning. Currently, we are seeking a highly talented and motivated PhD student within the field
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research group “Machine Learning for Biomedical Data” led by Prof. Dominik Heider and is embedded in the DFG-funded Collaborative Research Centre 1748, Principles of Reproduction. The CRC 1748 involves
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mechanisms and kinetics to stabilize highly active but metastable surface motifs sustainable catalytic processes. Modeling Atomic Processes on Nanoparticles Develop atomistic models and machine-learning
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sciences or similar Strong interest in single-cell nucleus RNA-seq techniques / Perturb-Seq / Crop-Seq Willingness to learn computational biology/bioinformatics High motivation for scientific work and
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, Italy, SSM is a prestigious institution of higher learning and research with a deeply rooted interdisciplinary approach and a global perspective. Renowned for its rigorous selection process, SSM admits