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projects funded by the Horizon Europe and Clean Aviation programmes. Your qualifications as an Ingenious Partner: Master or (preferably) Ph.D. level qualification in Electrical, Aerospace Engineering
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(or equivalent qualification) in neuroengineering, computer science, mathematics, electrical engineering or a related field Strong analytic skills and experience in signal processing and machine learning Excellent
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and graph learning frameworks such as PyTorch, PyTorch Geometric. Knowledge in the field of drug discovery/molecular property prediction and recommender engines (especially using graph learning methods
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of charge. Fair salary: The basic salary of EUR 3.071,3 increases if we can credit professional experience. Equal opportunities for everyone: We look forward to diverse personalities in the team! It’s
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As Austria's largest research and technology organisation for applied research, we have set ourselves the goal of making substantial contributions to solving the major challenges of our time
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for precise interventions in the human microbiome and thus create the basis for chemical microbiome engineering for the future. Our international team is characterized by open, respectful cooperation, excellent
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supports a safe, equitable, and sustainable approach to tackling AMR. Anchored in Science and Technology Studies (STS) research perspectives, ALTERBIOTIC analyses the entanglements and the tensions between
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ecosystem that supports a safe, equitable, and sustainable approach to tackling AMR. Anchored in Science and Technology Studies (STS) research perspectives, ALTERBIOTIC analyses the entanglements and the
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(prae doc), for a period of 4 years, focusing on process mining. The selected prae doc will become part of the Research Group Workflow Systems and Technology (WST) at the Faculty of Computer Science and
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role across a wide range of fields, from physics and biology to finance and engineering. But there's a catch: in most real-world scenarios, this equation lives in very high-dimensional spaces, making its