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knowledge of machine learning (e.g., in the areas of object detection and identification, generative AI, etc.) Good written and spoken English skills (min. level B2) Good written and spoken German skills (min
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and sensor data processing, bioinformatics, systems biology, or biophysics. Familiarity with simulation environments, numerical methods, or machine learning approaches is an advantage. Fluent command
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Lehrstuhl für Nachhaltige Thermoprozesstechnik und Institut für Industrieofenbau und Wärmetechnik | Aachen, Nordrhein Westfalen | Germany | about 2 months ago
. Methodological knowledge in the field of machine learning is an advantage. You have a high level of independence and commitment. You would like to develop and realise your own ideas. You enjoy working in a team
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strengthen the data science and machine learning activities of the IAS-9 with exciting new topics. You will work in a multidisciplinary team of enthusiastic data scientists, software developers and domain
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machine learning tools for the efficient analysis of the experimental data. For more information, visit our web page www.soft-matter.uni-tuebingen.de We are looking for a motivated PhD student to contribute
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-weighted and functional MRI, intracranial EEG) Multi-scale modelling of human brain development Using machine learning frameworks to interrogate the relationship between brain development and cognitive
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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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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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, prototyping, programming (device communication, databases) Experience in the following areas is also a bonus: electrocatalysis, rheology, coating technology, machine learning Intrinsic motivation to show
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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