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based on different weather conditions. The researcher will also work with team members within the consortium in generating necessary data required for developing a machine learning model for storm surge
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multidisciplinary research team of Dr. Akhilesh Pandey at Mayo Clinic, Rochester, working at the intersection of digital pathology, artificial intelligence (AI), and machine learning (ML). This position
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scalable machine learning and AI tools that integrate spatial multi-omics data with mechanistic models across molecular, cellular, and tissue scales. The postdoc will also have the opportunity to make major
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, machine learning, data science, drug discovery, and related fields are encouraged to apply. Strong computational backgrounds (AI/ML foundation models), proficiency in at least one programming language
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simulations and machine learning for the development of functional material. Assisting the PI to work on the research project and initiate the new projects and to also provide training assistance for the
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CIC bioGUNE (Asociación Centro de Investigación Cooperativa en Biociencias) | Bilbao, Pais Vasco | Spain | 26 days ago
goal, the candidate will combine a gene network-based approach with a machine learning model (foundational model) to propose protocols for the sequential induction of transcription factors to
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metabolomics - to interpret complex biological datasets and derive actionable insights. 4. Experience applying artificial intelligence (AI) or machine learning (ML) approaches to protein or genetic circuit engineering. Req ID: 32139 Apply now
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experiments, fluid-structure interactions, sensors for offshore structural health monitoring, software development, machine learning and advanced AI modelling, and previous experience of working in large
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will also have access to substantial compute resources that can be leveraged to further accelerate progress, including scientific compute, bioinformatics, and machine learning. The environment at GBI
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will also have access to substantial compute resources that can be leveraged to further accelerate progress, including scientific compute, bioinformatics, and machine learning. The environment at GBI