462 machine-learning "https:" "https:" "https:" "https:" "https:" Postdoctoral positions
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, including the ultra-high-resolution Energy Exascale Earth System Model (E3SM), the machine learning emulators ACE-ERA5 and ACE-E3SM, and the regional Energy Research and Forecasting (ERF) model. The work
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effect. Bhat group The position will involve developing new mathematical/computational methods at the intersection of scientific computing and machine learning. At a high level, the project is to
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project will develop general self-supervised and unsupervised machine-learning methods for biological data where reliable labels are scarce, expensive, or impossible to obtain. The aim is to build methods
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used for data analysis, such as R or Python. • Experience with single-cell or spatial transcriptomic analysis is desirable. • Experience with machine learning, LLMs, AI agents, multimodal data
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-scale in vivo perturbation experiments to uncover how genes shape immune-cell states and predict how the immune system responds to interventions. This tight integration of advanced machine learning and
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; Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL). 1 - Cumeras, R., T. Shen, L. Valdiviez, Z. Tippins, B. D. Haffner and O. Fiehn (2023). "Differences in the Stool Metabolome between
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intersection of robotics, control engineering, machine learning, and neuro-inspired computing, while collaborating closely with academic partners and researchers across disciplines in Denmark as well
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, combinatorial optimization or Bayesian network analysis Large language models or machine learning/predictive modeling for longitudinal data analysis Strong computer programming skills Strong mathematical
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About the Opportunity Conduct research on machine learning, control theory, and synthetic biology. The work will combine tools from dynamical systems, control theory, and the theory of algorithms and
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recent advances in genetics and genomics, and through collaborations with groups using machine learning. We are developing and applying tools to understand how implicated genes act in neurons and