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Field
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optimiser that accelerates both workflow efficiency and materials discovery. Main Tasks and responsibilities: Own the optimiser: design, implement, and tune heuristic/metaheuristic algorithms (e.g
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programming (Python, MATLAB), neural networks, deep learning or physiological signal analysis. - Minimum of 2 years of accredited professional or research experience in tasks directly related to: AI algorithm
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background in computer science or biomedical engineering, with a strong focus on programming using deep learning libraries and machine learning algorithms. Demonstrated experience in medical image processing
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these data structures and their associated algorithms to enable pattern-matching and other operations required, for instance, to infer microbial transcriptional regulatory networks through comparative genomics
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optimiser that accelerates both workflow efficiency and materials discovery. Main Tasks and responsibilities: Own the optimiser: design, implement, and tune heuristic/metaheuristic algorithms (e.g
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offer a PhD student position at the Universitat de Barcelona (as part of the PhD Program in Mathematics and Computer Science) to develop new AI and federated learning algorithms for diagnostic imaging in
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pathways, including deactivation processes. Screening and fine-tuning catalysts to enhance performance. Developing workflows and machine learning algorithms to accelerate catalyst design (optional). Group
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y 6g. ----------------------------- Support in research studies and development of prototypes for confidentiality and secure authentication using quantum resistant asymmetric algorithms. Application
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&D&I ACTIVITIES IN THE RESEARCH AREA OF GENETIC IMPROVEMENT OF BIOLOGICAL CONTROL AGENTS. (C-083/25). More information: https://tablon.upct.es/anuncio/ QNjBXkq O Pz Deadline for submission
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scientific information to create classification strategies that tailor interventions to the underlying mechanisms of disease in specific patient subgroups. Most pediatric genetic diseases—such as