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Field
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the use of machine learning and AI approaches • Integration of proteomics with genetic data via MR, coloc and FUSION to identify causal and druggable targets Requirements • The successful applicant will
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in data integration, model design, and large-scale training by combining multi-modal scientific data, knowledge graphs, physics-aware machine learning, and GPU/HPC computing to develop transparent and
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minimum 5 years’ experience in epidemiology, data management, programming and statistics at supervisory level. Proficiency in SQL, Python/R, or similar tools; experience with big data platforms , machine
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and have synergiccollaborationeffects. Weexpect a motivatedearlycareer researcher with stronginterest and experience with GIS/earth observation/climateprojection data as well as machine learning models
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of machine learning and computational approaches to modeling human learning and language, normally acquired through attainment of a PhD in Computer Science or equivalent formal training in similar field
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data analysis is required. The lab mostly uses R for data analyses; knowledge of R is not required, and the postdoctoral scholar will have the opportunity for mentorship and learning. To Apply: Motivated
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Are you passionate about using data science and machine learning to address mental health inequalities in rural and coastal communities? The University of Lincoln is seeking an ambitious
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Data Scientist (Artificial Intelligence). We now invite applications for the captioned post. Duties and Responsibilities Develop and apply advanced artificial intelligence and machine learning models
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; mechanism design and institutional design; cooperative AI and multi-agent systems; the study and development of large language models; cross-cultural psychology and large-scale behavioral data; philosophy
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functional genomics, bioinformatics, and machine learning to support the generation, interpretation, and screening of large-scale experimental and computational outputs. The successful candidate will