502 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"UCL"-"UCL" positions in Germany
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• numerical simulations and computer programming (e.g., Python and LabVIEW) • Developing back-of-the-envelope estimates for complex physical problems. Applications should be sent by e-mail, together
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students who would like to write their final thesis in the field of machine learning / computer vision. The primary goal of this master’s thesis is to develop an algorithm that can accurately and efficiently
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Machine Learning Cluster of Excellence TERRA CIN LEAD Graduate School & Research Network Collaborative Research Centers Transregional Collaborative Research Centers (CRC-TRRs) DFG Research Units Research
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manufacturing and laser material processing. We are currently developing machine learning-based approaches to make the laser powder bed fusion (LPBF) process more efficient and improve its quality. To this end, a
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• experience with molecular techniques (e.g., gPCR, RT-gPCR, nucleic acid extraction) • basic knowledge of metabolome analysis or willingness to learn • high motivation to contribute to animal welfare and
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Max Planck Institute for Dynamics and Self-Organization, Göttingen | Gottingen, Niedersachsen | Germany | about 1 month ago
physics is a plus. Programming skills are highly desirable. Fluency in both written and spoken English is required. The researcher should show eagerness to learn new skills and apply established ones.
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or similar object-oriented programming languages. Experience with machine learning/statistical methods applied to time series data is advantageous. Familiarity with databases, containerization, and knowledge
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“you” culture 🖥 Workplace: Excellent equipment with machines and devices 💪 Co-design: Independent project management and room for innovative ideas in applied research 🧘♀️ Work-life balance: Benefit
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to environmental cues. Innovation drivers include the development of advanced technologies and the full integration of complex computational approaches to answer relevant biological questions. To learn more about
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and/or AI-based approaches), including the integration of concepts such as reinforcement learning and multi-agent reinforcement learning Further development and use of virtual test environments