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profound knowledge in computational and theoretical physics/chemistry. Capability of team work is essential. Skills in high-performance computing, materials chemistry, theoretical chemistry, molecular
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Conservation Soil Science of Temperate Ecosystems Soil Science of Tropical and Subtropical Ecosystems Molecular Wood Biotechnology and Technical Mycology Silviculture and Forest Ecology of the Temperate Zones
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the project “Modeling Great Ape Signaling Behavior” under the auspices of the Collaborative Research Center “Common Ground” (CRC1718), which is funded by the German Research Foundation (DFG), at the University
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) Research area: Large Language Models (LLMs), knowledge graphs (KGs), commonsense knowledge Tasks: foundational or applied research in at least one of the following areas: LLMs, KGs, knowledge extraction
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the training of state-space models Collaborate closely with our internal partners at PGI-14 (Neuromorphic Hardware Nodes) and international academic and industry partners Publish research articles and regular
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University of Veterinary Medicine Hannover • | Hannover, Niedersachsen | Germany | about 17 hours ago
Systemische Neurowissenschaften). Courses covering the following subjects are offered: Basics of cellular and molecular neuroscience Sensory systems (auditory, olfactory, and visual) Cognitive and behavioural
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susceptible steel structures. Thus, the candidate will develop reliable machine learning-based surrogate models to replace expensive phase field models to simulate failure because of HE. The activities will be
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such as the NEPS. Potential research areas include (but are not limited to): Item response modeling of achievement tests Analysis of process data (e.g., response times) to enhance competence measurements
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. Qualifications The successful candidate (m/f/d) should hold a Master's degree or similar qualification in Biochemistry, Biology, Molecular Biology or Life Sciences, Pharmaceutical Sciences, or related fields
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– from the modeling of material behavior to the development of the material to the finished component. PhD Position in Machine Learning and Computer Simulation Reference code: 50145735_2 – 2025/WD 1