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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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, 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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NDT data, machine learning models, and RFID-enabled traceability systems. Prepare and draft technical reports, conference/journal papers, and presentation materials; present research findings to
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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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control: process modelling, control, and optimization, with applications in chemical and pharmaceutical manufacturing; data-driven modelling and machine learning applications in process industries
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CIC bioGUNE (Asociación Centro de Investigación Cooperativa en Biociencias) | Bilbao, Pais Vasco | Spain | 16 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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What is your preferred job type? required Bioinformatician Director Editor Engineer Faculty Member Head of Department Health Professional Internship Lecturer Manager Marketing PhD Studentship
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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