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play a central role in this interdisciplinary initiative. They will: Develop and apply machine learning (ML) methods – including surrogate modeling, feature extraction, and inverse design algorithms
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disciplines strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation and the ability to work independently with
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direction (possibly forming spontaneous “lanes”), crossing, and opposite flows. For single-lane vehicular traffic, the model should revert to a car-following model. In cooperation with the supervisor Dr
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Universität Berlin. The position is part of the research group QUALITY.2 (Phytonutrient Management) in the programme area ‘Plant Quality and Food Security’ (QUALITY). The aim of the research project “PhytoM” is
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, artificial intelligence, and security, with a focus on tools and techniques for constructing reliable, efficient, and secure software. General areas of research include: Artificial intelligence to reason about
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written and spoken English skills High degree of independence and commitment Experience with machine learning and high-performance computing is advantageous, but not necessary Our Offer: We work on the very
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between quantum computers (via Qiskit) and classical HPC resources Validate the QCS-MiMiC implementation on IBM’s ibm_cleveland quantum computer by reproducing recently published benchmark QM / MM
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‑time. You will benefit from our family‑friendly and collegial atmosphere, our established health management and occupational pension provision. As a public funded employer, we offer you a secure
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learning, image analysis, and advanced computing to study relationships between structure and function. Keywords: Human Brain, 3D Atlas, Deep Learning, Temporal Lobe, Brain Function Entry Requirements
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vitro and in vivo ) A lively scientific community and a corporate culture of appreciation & promotion of equal opportunities Flexible working hours, part-time models 30 days of vacation Social security