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employees with Greenland as our primary base for Arctic science activities, and we are strongly anchored in the Greenland Ecosystem Monitoring (GEM) programme and to research and advise related to industrial
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Profile Leading Researcher (R4) Application Deadline 3 Sep 2026 - 21:59 (UTC) Country Denmark Type of Contract Permanent Job Status Full-time Is the job funded through the EU Research Framework Programme
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to shared tasks within the section and department, including industry collaboration, study programme development, and supervision of projects associated with externally funded activities. Your competencies
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funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description ATTENTION: Contact persons
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sustainable food production, environment, climate, health and welfare for animals and humans. The activities form the basis for the research-based public sector consultancy and degree programs covering
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Corporate finance Finance Operations management Candidates are expected to teach and supervise students at bachelor’s and master’s levels. Our study programme portfolio includes MSc programmes, a bachelor’s
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Starting Date 1 Sep 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer
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proficiency in two or more relevant programming languages (e.g. Python, R, SQL, Julia or others) a flair for technical tasks involving hardware and software, troubleshooting, firmware updates and maintenance
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professor must complete Aarhus University’s teacher-training programme for assistant professors , which is designed for university teaching. Tenured associate professor We are looking for applicants with
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Two DTU Tenure Track Assistant Professors in Autonomous Modelling and in Robotic Synthesis of Ene...
and robotics. As the successful candidate, you will develop innovative research programs spanning atomistic and mesoscopic materials simulations, machine learning, foundation and surrogate models