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; T2: State-of-the-art review and model testing; T3: Development of algorithms for information extraction; T4: Algorithm testing and validation; T5: Preparation of reports, presentations, and other
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Genomics at Harvard Medical School Several positions are available in the Park Lab (https://compbio.hms.harvard.edu/ ). The aim of the laboratory is to develop and apply innovative computational methods
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Are you interested in developing interpretable AI models for the next generation of green syntheses? Do you have experience in AI/Machine Learning, or computational modelling of organic reactions
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-machine teaming. Moreover, the consequences of such digital transformation are explored in the context of workforce and labor developments, organisational innovation, and learning/education. About the
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, and computer graphics, to identify existing research, methodologies, and advancements. Designing and developing innovative algorithms, models, and techniques for solving complex problems in computer
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programme Reference Number AE2025-0527 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2025-0527
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programme Reference Number AE2025-0550 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2025-0550
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Postdoctoral Research Fellow in Multimodal Foundation Models and Biomedical AI – AI/CS-Oriented Role
Develop and implement novel AI models and learning algorithms for multimodal and generative modeling. Collaborate with neuroscientists, clinicians, and AI researchers on interdisciplinary problems involving
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Postdoctoral Research Fellow in Multimodal Foundation Models and Biomedical AI – AI/CS-Oriented Role
Develop and implement novel AI models and learning algorithms for multimodal and generative modeling. Collaborate with neuroscientists, clinicians, and AI researchers on interdisciplinary problems involving
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, inaccessible to standard techniques. To probe such regimes requires the development of fast and scalable algorithms for many-component systems, and of coarse-grained models that can be analyzed and simulated