1,053 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"ISCTE-IUL" Fellowship positions
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Field
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responsibilities will include: Explore innovative methods for food process optimization including the use of AI and machine-learning Develop and execute methods for characterizing and linking the texture and
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, and AI/machine learning would be helpful for the role. Experience with participant recruitment and retention as well as clinical human subject studies is a plus. Special Instructions Application
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review. You will receive training in advanced statistical methods for safety signal detection, machine learning applications in pharmacovigilance, and evidence synthesis techniques. You will collaborate
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statistical and machine learning modeling to conduct data analyses for large-scale multimodal (genomics, omics etc) studies. Conceptualise new ideas, lead data-driven discoveries, ensuring in-depth assessment
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and Knowledge: Experience in computational catalysis and surface science. Preferred Qualifications: Knowledge of kinetic modeling and/or machine learning interatomic potentials. Background Investigation
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What You’ll Need: PhD in computer science, artificial intelligence, machine learning, computational biology, biomedical engineering, or a closely related quantitative field. Strong foundation in modern
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’. The role-holder will work closely with medicinal chemists at University of Oxford and pharmacologists at University of Glasgow, applying virtual screening, machine learning, AI-driven generative chemistry
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application of innovative Machine Learning (ML) frameworks to understand and predict the global hydrological cycle. The role will require bridging the gap between process-based physical modeling and scalable
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Computer Science, Artificial Intelligence, Software Engineering, or a related field. Strong programming proficiency in Python and/or C++. Demonstrable experience with machine learning frameworks (e.g., PyTorch
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behaving mice, and advanced modeling + machine learning analyses. Please read more about our research at www.apostolideslab.org . Key questions we want to answer are: How do neural circuits extract