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for data science (Python, R, SQL, PostGIS, GeoPandas, etc.). Knowledge of urban models and spatial analysis tools (urban growth models, accessibility, change detection, etc.). Ability to work with
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Research Associate position, with the possibility of extension based on an annual basis dependent upon satisfactory performance and the availability of funding. This position is part of the Preventive
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and compare material intralogistics handling alternatives—such as in-pit crushing & conveying, trolley-assist systems, and battery-electric trucks—in strip mining operations. This research is part of
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Ref.: 532732 Work type: Full-time Department: Centre for Information Technology in Education within the Faculty of Education (10001) Categories: Senior Research Staff & Post-doctoral Fellow Full
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intelligence, AI-based data analysis, transcriptomics, proteomics, genomics or spatial omics. Interdisciplinary background or interest. A focus on Wet Lab research development. Candidates with experience
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Postdoc Appointment Term: Position for 1 year, extendible based on performance. Appointment Start Date: 1/16/2024 Group or Departmental Website: https://oncology.stanford.edu/ (link is external) How
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journals. Experience with stereotaxic surgery and circuit-level manipulations is highly desirable. Communication skills the ability to work both independently and as part of a team. Why Join Us: Work in an
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to work independently, take initiative in moving a research project forward, and effectively manage time to meet deadlines in a remote environment Desirable qualifications: Strong data management, analysis
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funded for 4 years by EU Horizon RIA with partners in Denmark, Germany, and France. You will be part of our team aiming to develop and utilize advanced X-ray techniques in the ultrafast time domain
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validate polarizable force field models. Responsibilities will include both macroscopic property analysis (e.g., density, diffusion coefficients, ion conductivity, interfacial tension) and atomistic-level