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Max Planck Institute for Mathematics in the Sciences | Leipzig, Sachsen | Germany | about 22 hours ago
Research Group "Cluster Algebras" of Dani Kaufman has openings for PhD Student and Postdoctoral Researcher Positions. The group is based at the Max Planck Institute for Mathematics in the Sciences, a
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and Environment (IEE-USP). Requirements: 1. Proven experience in statistical analysis (regression and cluster analysis); 2. Previous research on aging and sleep; 3. Background in Social Sciences in
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structural development over time at the group, sub-group, and individual level (e.g., using normative modelling and clustering approaches to parse heterogeneity). The candidates will further have the
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structural development over time at the group, sub-group, and individual level (e.g., using normative modelling and clustering approaches to parse heterogeneity). The candidates will further have the
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computational workflows on a high-performance cluster. You will test hypotheses using data from multiple sources, refining your approach as needed. The role also involves close collaboration with colleagues
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ecosystem; contribute to the mentoring of trainees within the lab; publish peer reviewed manuscripts and contribute to funding proposals. Educational Requirements • PhD in Chemistry, Bioinformatics
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. The Department is also part of the Austrian Science Fund Cluster of Excellence "EurAsian Transformations" and hosts both the Center for Interdisciplinary Research and Documentation of Inner and South Asian
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or equivalent and a PhD (or close to completion) in computer science, math or comparable, or an applied/life science (e. g. engineering, biology, medicine) with a focus on data analysis and/or machine learning
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-funded consortia FOODGUARD (www.foodguard-project.eu/ ) and NUTRIMMUNE, the Cluster of Excellence “Balance of the Microverse” (www.microverse-cluster.de ), the CRC/Transregio 124 “Pathogenic Fungi and
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computing AI on High-Performance Computing (HPC) cluster. Examples on areas of research interest include but are not limited to: Vision transformers. AI foundation models. Computing and energy-efficient