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datasets generated by PIV and PLIF experiments to determine the effects of rotation on mixing efficiency and solute deposition. You will develop scripts for data processing and visualization, providing
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DC-26094– POSTDOC/DATA SCIENTIST – AI-DRIVEN CLIMATE RISK MODELLING AND EARLY WARNING SYSTEMS FOR...
: https://www.list.lu/ How will you contribute? You will be part of LIST’s Remote sensing and natural resources modelling group Embedded in the Environmental Sensing and Modelling (ENVISION) unit
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http://orcid.org/ ) Teaching portfolio including documentation of teaching experience Academic Diplomas (MSc/PhD) Applications received after the deadline will not be considered. All interested
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and expertise with the following software: Microsoft Office Suite, specifically Microsoft Word, Microsoft Excel, PowerPoint, Publisher and Outlook. Physical Demands and Work Environment Content will
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processing, quality control, integration, and analysis of single‑cell and multimodal omics datasets (e.g. scRNA‑seq, scATAC‑seq). Train, evaluate, and benchmark deep learning models operating on single‑cell
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 11 hours ago
. The department’s operating budget is 27 million a year. Position Summary The Postdoctoral Research Associate will be involved in manuscript preparation and curation of software in support of grant aims. They will
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at scientific conferences and by writing scientific articles and a PhD thesis; attending PhD courses as part of the graduate education program. Where to apply Website https://www.academictransfer.com/en/jobs
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students and contributing to an inclusive, collegial research environment. Application Materials Application Process: Apply online at https://hr.missouri.edu/job-openings , Job ID# 58263. Applicants should
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about the ISSE Institute, please visit our website: https://www.isse.tu-clausthal.de Your responsibilities include: Research and development in the field of software engineering for dependable and safe
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processing, quality control, integration, and analysis of single‑cell and multimodal omics datasets (e.g. scRNA‑seq, scATAC‑seq). Train, evaluate, and benchmark deep learning models operating on single‑cell