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postdoctoral Research Fellow (RF) position for one year with a possible extension for one more year. The starting date is November or December 2025. This post will advance the application of Machine Learning (ML
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., MRI, EEG, and health records). Background in computational modeling and machine learning. Background Investigation Statement: Prior to hiring, the final candidate(s) must successfully pass a pre
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Build and test predictive models using machine learning techniques Drive methodological innovation in neurophysiological data analysis Contribute to publications, grant submissions and independent
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will join a team of probabilistic modellers and machine learning researchers developing new collaborative AI principles and methods. This is an exciting topic which inspires new problems in fundamental
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Supervised Machine Learning and Reinforcement Learning. The objective is to significantly enhance battery performance and longevity. While conventional methods rely on either physics-based models or high-level
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, and semi-structured interviews. Using European competence models (e.g., GreenComp, LifeComp), the project will develop flexible lifelong learning models that universities can adapt to different
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Responsibilities: Conduct programming and software development for data management. Design and implement machine learning models for optimizing data management. Conduct experiments and evaluations of the designed
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systematic perturbation approaches. Systems Biology: Integrate multi-omic datasets to map the molecular networks influenced by mito-MPs. Machine Learning: Apply cutting-edge protein language models and AI
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). The objective of this project is to enhance malaria control programs in Peru, Ecuador, and Brazil by expanding and improving early warning and surveillance systems, and modeling the impacts of coordinated
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Machine learning/AI based classifiers Proficiency in coding using R and Python and other similar languages High level analytical capability Ability to communicate complex information clearly Informal