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Field
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on type, size, location of data centers in the US, their electricity and water demand, carbon emissions; exposure to air pollution. ● Develop and/or apply methods for causal inference and machine learning
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, or sonar sampling of the benthos ● statistical fluency (e.g., mixed effects models, Bayesian statistics) applied to noisy field biomonitoring data or long-term ecological datasets ● experience operating and
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/instruction tuning methods. * Understanding of Reinforcement Learning (RL) principles, multi-objective optimization, or active learning/Bayesian optimization. * Strong programming capabilities in Python
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Max Planck Institute for Gravitational Physics, Potsdam-Golm | Potsdam, Brandenburg | Germany | 1 day ago
inference, including machine-learning methods. Astrophysics of compact objects and binary formation scenarios. Cosmography with gravitational waves: dark energy, dark matter and gravitational lensing. Tests
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heterogeneity in cancer, inflammation, and tissue senescence. • Developing next-generation deep-learning and statistical deconvolution methods for inferring gene regulation from bulk, single-cell, and spatial
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and deep learning methods for large-scale genomic, clinical, and imaging biobank data, with stable multi-year NIH support. The Zhi Laboratory has a sustained track record of methods development
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About the lab The Laboratory of Causal Systems Immunology combines causal inference, probabilistic AI and large-scale in vivo perturbation experiments to uncover how genes shape immune-cell states
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of medicine and therapeutics within the Department of Pharmacology and Therapeutics based in the Institute of Systems, Molecular and Integrative Biology. This programme aims to develop causal inference models
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or quantitative methods. We are open to a range of methodological backgrounds, including digital trace data analysis, natural language processing, machine learning, experimental design, causal inference, and
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to ethical and reproducible research. Relevant experience may include network measurement, mobile systems, browser instrumentation, distributed experimentation, statistical analysis, causal inference, large