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work. Qualifications PhD in computer science, computational biology, engineering, or related fields. Experience developing deep-learning tools for image processing, automatic monitoring of agricultural
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Sciences Startdate: 05.05.2026 | Working hours: 40 | Collective bargaining agreement: §48 VwGr. B1 lit. b (postdoc) Limited until: 25.08.2026 Reference no.: 5082 Explore and teach at the University of Vienna
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assisting with in-situ TEM measurements, facilitating cutting-edge research in sustainability and energy fields. Part of the project will also include the development of deep learning frameworks for TEM image
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and energy distributions at the substrate level, as well as deep knowledge of plasma-surface interactions. - Strong written and oral communication skills; ability to work independently and as part of a
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curiosity and a deep sense of duty, they contribute invaluable insights to research and teaching, enriching our society. Are you inspired and driven by the desire to make a meaningful impact? We are currently
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7,700 academic staff members, who passionately pursue answers to the profound questions that shape our future. Fueled by curiosity and a deep sense of duty, they contribute invaluable insights to research
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environments (Gazebo, Unreal Engine, or Unity). You have experience in artificial intelligence (Deep Learning, PyTorch) or embedded systems (ROS2, FPGA/VHDL design). You are curious, show scientific rigor and
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science. Teach relevant courses, supervise BSc, MSc and PhD students, and mentor postdocs and tenure track assistant Professors. Contribute to the strategic development of the department’s research and
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POSTDOC JOBS: HUMAN COGNITIVE NEUROSCIENCE Requisition # 4543 Position Basics Advertising Ends on:Saturday, March 28th, 2026 Advertising Started on:Tuesday, February 10th, 2026 College:College
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and paleosols 3) train and test deep learning algorithms. You will be required to take responsibility for all the steps involved in the “Phytolith analysis” work package of DEMODRIVERS. This will