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convection. The objective is to develop reduced but realistic models of cumulus life cycles that may be applied toward cumulus parameterization and/or machine-learning algorithms for predicting short-term
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Eligibility criteria Selection will be based on the following scientific and technical criteria: • PhD in computational biology, machine learning, bioinformatics or a related field. • Proficiency with Python
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stimulation (TMS), and transcranial direct current stimulation (tDCS) through interdisciplinary collaborations. Behavioral measurements and physiological recordings, including facilities for computer-based
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their added value against simpler machine-learning baselines; train and evaluate ARCA on large-scale microbiome datasets, with attention to sparsity, batch effects, scalability, generalisation across studies
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Faculty of Computer Science Startdate: 31.12.2026 | Working hours: 40 | Collective bargaining agreement: §48 VwGr. B1 lit. b (postdoc) Reference no.: 6223 Among the many reasons to research and teach
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against simpler machine-learning baselines; • train and evaluate ARCA on large-scale microbiome datasets, with attention to sparsity, batch effects, scalability, generalisation across studies and
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/nanoplastics, and other environmental compounds to assess their potential impacts on human health and the environment using machine learning (ML), deep learning (DL), and big data analytics. His lab is
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of teaching and learning. Mines has the highest admission standards of any university in Colorado, and the AMS department confers Bachelor’s, Master’s, and PhD degrees in applied mathematics and statistics
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skills, including generalized linear models, multiple machine‑learning algorithms, MOFA and multi‑omics pathway analysis. · Strong background in experimental design, quantitative data analysis, and
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at the Department of Biosystems Science and Engineering (D-BSSE) of ETH Zurich in Basel invites exceptional candidates to apply for a Postdoc position in pioneering projects at the intersection of synthetic biology