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in modeling and analysis of cyber-physical systems At the Technical Faculty of IT and Design, Department of Computer Science, a full-time postdoc position in modeling and analysis of cyber-physical
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Aarhus University is seeking three postdoctoral fellows for research on metabolic dynamics and pl...
. This project pursues approaches probing the systems-level plasticity of pure cultures of acetogens upon physical-chemical perturbations during syngas fermentation. This project involves detailed mechanistic and
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Application Deadline 1 Jun 2026 - 12:00 (Europe/Copenhagen) Country Denmark Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU
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communication and computation co-design enables scalable interaction among networked AIs, paving the way toward embodied intelligence in large-scale physical systems. Your competencies Prospective applicants
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, this position offers a unique opportunity. You will work with real robots, real sensors, and real physical interaction problems, contributing directly to the development of autonomous mining systems capable
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research profile within organisational studies, Computer-Supported Cooperative Work, Human-Computer Interaction or related research areas as documented by a PhD dissertation and/or research publications
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the systems-level plasticity of pure cultures of acetogens upon physical-chemical perturbations during syngas fermentation. This project involves detailed mechanistic and systems-level studies including, but
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, and train deep learning models on the resulting data to design new antibiotic compounds that evade both current and likely future resistance mechanisms. Your computational work will directly steer
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spintronic-based computing. The position offers an exciting opportunity to join a cutting-edge research project focusing on the co-design of CMOS and spintronic devices for next-generation energy-efficient and
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at the Department of Electrical and Computer Engineering, Aarhus University, where we are advancing communication-efficient and distributed foundation model inference across the computing continuum