930 machine-learning-"https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" uni jobs at Nature Careers
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. Iavarone to write and win competitive postdoctoral grants. Requirements: Medical degree or Doctoral degree and life science research experience. Technical aptitude for learning and executing complex
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implementing new informatics tools and resources to enhance phenotyping performance or enable deep phenotyping through terminology/ontology, natural language processing, and machine learning. The role involves
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teach at the University of Vienna, where over 7,500 brilliant minds have found a unique balance of freedom and support. Join us if you’re passionate about groundbreaking international research and
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building projects required. Experience with computer-aided drafting (AutoCAD) and Microsoft Office (e.g., Excel, Word, PowerPoint). Familiarity with current technical environmental impact assessment
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fellows at the University of Tennessee Health Science Center. Fellows receive a competitive salary, professional development allowance, a personal computer for use during the fellowship, tuition assistance
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models (e.g., deep learning, reinforcement learning, probabilistic graphical models) for applications in genomic prediction, GWAS, GS, gene-editing target discovery, and multi-trait selection. Conduct
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similar education that teach candidates to work safely in chemistry lab. We seek detail-oriented applicants that can work in a team. The ideal applicant is not afraid of proposing own ideas to help us solve
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of Recommendation. Letters of Recommendation should be submitted directly from the professional references via email to facultyjobs@jax.org . Application Resources: Please visit the Faculty Recruitment page to learn
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, advanced communication devices, advanced manufacturing, microfluidics, and more. 3) Intelligent and Bionic Systems: Molecular machines, adaptive micro-/nano-robots, bio-inspired systems, wearable electronics
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often struggle with domain shift, limited generalization, and the gap between simulation and deployment. These challenges motivate the development of advanced spatio-temporal learning frameworks that can