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environment. Other Required Skills and Abilities Demonstrated ability to manage and analyze large, multi-modal datasets. Familiarity with cloud computing environments (e.g., Google Cloud) and version control
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quantitative and computational social science, addressing a diverse array of new data and analytic challenges, facilitating impactful multidisciplinary collaboration, scholarly advancement, and the creation
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Austrian Academy of Sciences, the Austrian Archaeological Institute OeAI | Austria | about 2 months ago
into a multidisciplinary work environment, and strong team spirit Good computer skills, especially experience with CAD and 3D modelling software, and processing of 3D point clouds Willingness to travel
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with PyTorch, required to have experience developing code with a team through collaborative version control Experience working with large datasets and cloud computing environments. Solid background in
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of collaboration with top researchers within cybersecurity, networking, AI planning, and cloud computing, both within our department and two other universities in Sweden (KTH and Umeå University). The project is
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directions. This position is not eligible for H-1B visa sponsorship. Qualifications Minimum Requirements • Ph.D. in Transportation Engineering, Civil Engineering, Computer Science, Electrical Engineering
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Max Planck Institute for Extraterrestrial Physics, Garching | Garching an der Alz, Bayern | Germany | 3 months ago
Job Code: 04/2026 Job Offer from February 02, 2026 Astrochemistry Postdoctoral positions on Computational Chemistry (m/f/d) Job ID: 04/2026 The Max Planck Institute for Extraterrestrial Physics (MPE
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Code 9546 Employee Class Acad Prof and Admin Add to My Favorite Jobs Email this Job About the Job Position available in the laboratory and research program of Dr. Lin Yee Chen at the University
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Proficiency in R or Python Minimum of two years of experience in computational biology or cancer genomics Experience with high-performance or cloud computing (e.g., HPC, AWS, GCP) At least one first-author peer
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of the largest pan-cancer signaling models in the literature. SPARCED is compatible with high-performance and cloud computing, can simulate thousands to millions of single-cell trajectories, is easily expandable