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) for engineered microbial strains. Design and implement machine learning algorithms to predict strain performance and optimise metabolic pathways. Integrate multi-omics datasets into computational workflows
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candidate will: Develop genome-scale metabolic models (GEMs) for engineered microbial strains. Design and implement machine learning algorithms to predict strain performance and optimise metabolic pathways
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With success stories ranging from speech recognition to self-driving cars, machine learning (ML) has been one of the most impactful areas of computer science. ML’s versatility stems from the wealth
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About the role: We are seeking a senior learning designer or experienced educator with relevant experience to work on the design, development, and delivery of a new MSci blended on-campus programme
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accelerated AI, machine learning, and robotics algorithms with a strong focus on computational efficiency, memory reduction, and energy-aware deployment. The role targets foundation models, including large
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Working Title: Peer Learning Assistant - FWS State Role Title: Institutional Employment/Federal Work Study Position Type: Federal Work Study Position Status: Part-Time FLSA Status: Non-Exempt
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If you are a current Barnard College employee, please use the internal career site to apply for this position. Job: Lifelong Learning Instructor Job Summary: Barnard College, Office of Lifelong
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enhance the competencies of the Institute in one or more of the following research areas: foundation models and efficient training/adaptation methods on HPC systems, generative AI and multimodal learning
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About the position The Online Learning Specialist is based within the Library Learning Services (LLS) team. The role supports strategic initiatives aimed at improving library-related online learning
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REQUIREMENTS The Eberly College of Science, Department of Biology, is looking to hire Learning Assistants (LA) to provide support to Biology courses overseen by Teaching Faculty during the 2025-2026 academic