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Field
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. The calibration is typically based on a figure of merit derived from experimental data, such as the average gate fidelity provided by the randomized benchmarking protocol. In realistic scenarios, these quantities
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are using ferroelectric memories, which can calculate AI algorithms from the field of deep learning in resistive crossbar structures with extremely low power consumption and high speed. Furthermore, we
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- Model-based assessment of climate impacts on conflicting land use systems Reference code: 50139755_2 Commencement date: August 1st, 2025 Work location: Hamburg Application deadline: 04.06.2025 The Climate
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the field of biotechnology, bio-/chemical engineering, (bio) process engineering, bioinformatics, biophysics or biomathematics. Ideally you have Programming skills and knowledge on machine learning and
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an active student scene and a diverse cultural life. We are looking to fill a PhD position (m/f/d) - Improving understanding of seasonal and interannual carbon and water fluxes using process-based modelling
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At the Leibniz Institute of Plant Biochemistry in the Department of Bioorganic Chemistry a position is available for a PhD in Machine Learning for Enzyme Design (m/f/d) (Salary group E13 TV-L, part
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Description At the Leibniz Institute of Plant Biochemistry in the Department of Bioorganic Chemistry a position is available for a PhD in Machine Learning for Enzyme Design (m/f/d) (Salary group E13
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actual stress of helicopter components using a data-based as well as a physics-based approach. In the project “BIG-ROHU” (BIG Data - Rotor Health and Usage Monitoring), a system is being developed in
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(m/f/d) in the topic: “AI-based processing of CAD models for automated planning of computer-aided manufacturing.” The candidate has the opportunity to pursue a doctoral degree (Ph.D.). Remuneration is
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detection. One highly promising direction NV-based nano- and microscale nuclear magnetic resonance (NMR) spectroscopy. In our lab, this quantum sensor based NMR spectroscocopy is applied to life sciences as