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, Associate Professor in Biomedical Engineering. The researcher will join Dr McEvoy’s group, which brings together expertise in active cell biomechanics and in-vitro tumour models. The group’s overall focus is
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mammalian and bacterial expression systems and cell-based in vivo models of mechanotransduction. You will join a very lively and motivated international and interdisciplinary group of scientists. We use a
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IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava | Czech | 13 days ago
) at the IT4Innovations, in the Material Design group of Dr. Dominik Legut within the Modeling of Nanotechnology Lab, is open to applicants for the SPIN DYNAMICAL CALCULATIONS of the topics of Czech Science Foundation’s
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, Modeling, and Perceiving the Combinatorics of Groove-based Rhythms, funded by the Research Council of Norway. The project is affiliated with RITMO Centre for Interdisciplinary Studies in Rhythm, Time and
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their spatial patterns in varying environmental conditions. The successful candidate will integrate to the research unit « Microbial Oceanography - LOMIC : http://lomic.obs-banyuls.fr » in Banyuls sur mer, and
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for high-dimensional datasets, including spatial bulk and single-cell RNA sequencing, mass and flow cytometry, and imaging data derived from both patient samples and experimental models. The overarching aim
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position. Appointment Start Date: Ideally on or before July 1, 2026 Group or Departmental Website: https://med.stanford.edu/buckwalter-lab.html (link is external) https://med.stanford.edu/neurology/divisions
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: 281522549 Postdoctoral Associate: Integrating political economy insights into energy modeling D-26-SPI-00009 | Research | Princeton School of Public and International Affairs The Peng group in the School
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. Within this project, work package 1 focuses on the resilience of the marine sinks of heat and carbon, using Earth system and biogeochemical models, observational data, and scenario analysis to identify
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). The position will focus on using AI, particularly multimodal transformer-based deep learning models, to extract and leverage information from genomic and chemical structures. Applications include infectious