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Field
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and machine learning methods. Knowledge of constraint-based metabolic modelling will be considered a strong advantage. The ideal candidate is highly motivated, capable of working both independently and
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further both professionally and personally in an interdisciplinary setting. Position DWI is looking to fill the position as soon as possible: Research Scientist Machine Learning Engineer - AI-Powered Image
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seismicity in the area at unprecedented resolution. Leveraging and improving state-of-the-art machine learning techniques, template matching and other techniques, you will derive a high precision catalogue of
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hosts. The project is centered on the integration and analysis of multiomics datasets utilizing advanced machine learning approaches and biological network analysis. The successful candidate will join an
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research experience, preferably in programming languages, compilers, applied mathematics, and optimization techniques a strong background in compiler, code generation, and machine learning would be
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systems. We intend to develop ground motion models that integrate large-scale databases of observed ground motions, physics-based simulations of seismic waveforms and cutting-edge machine learning methods
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elements distribution, crystallographic texture), mechanical properties (hardness, yield and tensile strength) and corrosion profile (rate and localization). This work focuses on machine learning assisted
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applications. To achieve this, you will employ computational fluid dynamics (CFD) and machine learning (ML) to investigate degradation mechanisms under various operating conditions and develop strategies
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in medicine and other study programmes and graduate initiatives in which the Faculty of Medicine is involved is expected. Beyond the core research area, the appointee will also teach in all degree
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robotic system design, humanoid robot development, manipulation and bimanual manipulation, control, or machine learning for robotics. Excellent project management skills to meet and achieve the expected