35 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "Imperial College London" PhD positions at Leibniz
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the reference number 70-2025 until 15 December 2025 to (see button e-mail application below). https://jobs.zalf.de/jobposting/d605d23b356789a6ae4c7e49e70893988fff4ad40 If you have any questions, please do not
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the Forschungsverbund Berlin (https://www.fv-berlin.de/ ) and the Leibniz Association www.leibniz-gemeinschaft.de . You can find more details on the institute webpage: www.ikz-berlin.de . The SiGe-based Quantum Materials
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be found on our homepage: https://www.leibniz-bips.de/en . How to apply Please send us your letter of motivation and CV by November 7, 2025 by email as a single pdf to: bewerbung(at)leibniz-bips.de
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information at: http://www.ifw-dresden.de . The Institute of Metallic Materials at the Leibniz Institute for Solid State and Materials Research Dresden (IFW Dresden) offers a PhD-student-Position (m/f/div
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The Leibniz Institute for Neurobiology (LIN) is an internationally recognized neuroscientific research institute and dedicated to the research on learning and memory. Our research comprises all
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research project, and the training programme is available on the RTG webpage (https:// www.uni-goettingen.de/rtg2906). Applications are due by 15.01.2026. We ask you to submit your written application as a
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: active learning (uncertain cases first), smart sampling, confidence thresholds, gradations (auto-label/review/manual), measurement and decision logic for throughput vs. quality. Proficiency in programming
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Psychology, Neuroscience, or a related field Very good methodological and statistical skills Very good command of English (written and spoken) and willingness to acquire proficiency in German within the first
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: Dr. Phil Richter (p.richter.leibniz-lsb(at)tum.de ) or Prof. Dr. Veronika Somoza (v.somoza.leibniz-lsb(at)tum.de ) More information on the working group can be found here: https://www.leibniz-lsb.de
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), biostatistics, machine learning, data science and research data management, and causal inference methods (Iris Pigeot, Marvin Wright, Vanessa Didelez), and etiologic and molecular epidemiology (Konrad Stopsack