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. This opportunity will prepare candidates for a range of competitive positions in academia or industry that involve computational biology/chemistry, machine-learning for biological or chemical data, metabolism, and
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within the Department of Electrical and Information Technology works broadly with research within Cryptography, Computer Security, Wireless and Fixed Networks. The security group has around 20 members
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, ROS) Solid skills in numerical analysis Advanced knowledge of computer vision Experience in human–robot interaction Particularly Meritorious It is particularly meritorious if the applicant has: A PhD
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computing and/or cloud computing; familiarity with Earth system models through model development, model execution, and/or model performance diagnoses; applied mathematics methods such as machine learning
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collaborate with partners at ELLIS Institute Finland. Target publications at top-level AI, ML, and NLP venues. Who we are looking for Requirements Ph.D. in Machine Learning, Natural Language Processing
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experimental approaches such as non-coding CRISPR screens, the Massively Parallel Reporter Assay (MPRA), saturation mutagenesis, and synthetic sequence design, alongside machine-learning models of regulatory
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CeMM - Research Center for Molecular Medicine of the Austrian Academy of Sciences | Austria | 2 months ago
” models in the context of the Human Cell Atlas and the European Lab for Learning & Intelligent Systems , powered by large-scale single-cell, spatial, and CRISPR perturbation profiling; Tissue immunology
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domains such as telecom, defence and cloud. You will join the Machine-Intelligence for Networks and Distributed Systems (MINDS) research group at the Department of Computing and Learning Systems, School
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ageing studies and diagnostic measurements. Familiarity with machine learning and data analysis. Strong programming skills, for example in Python and/or MATLAB, and a strong publication record. What you
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analysis, GIS, and large environmental datasets Experience developing predictive or machine learning models for environmental systems Demonstrated record of peer-reviewed publications Experience