17 phd-in-computer-vision-and-machine-learning Postdoctoral positions at Nature Careers in France
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computational framework, integrated with deep reinforcement learning (DRL) methodologies for both gene-level and edge-level perturbation control, represents a significant advancement in the computational toolkit
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various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently work at the LCSB. We excel because we are truly
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found on hpc.uni.lu . The activities include classical HPC applications such as simulation and modeling, but also artificial intelligence and machine learning, bridging computational science, with data
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activities Present results in international conferences and workshops Your profile A PhD degree in Computer Science, Physics or a related field Strong background in understanding plasma physics and
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The candidate will have a PhD or equivalent degree in bioinformatics, biostatistics, computational biology, machine learning, or related subject areas Prior experience in large-scale data processing and
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various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently work at the LCSB. We excel because we are truly
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Learning within the Department of Education and Social Work at the University of Luxembourg. The person will be part of a team in the dynamic organisational context of a growing, globally connected research
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various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently work at the LCSB. We excel because we are truly
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Biology, or a related field. Strong experience in bioinformatics and next-generation sequencing (NGS) analysis in a Cloud computing environment is essential. Proficiency in Linux/Unix and scripting
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, Experience and Qualifications PhD in biochemistry, Biomedical Sciences or Chemistry. Mass spectrometry-based proteomics. Data analysis of large proteomics datasets. Experience in cell culture and molecular