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planning and control algorithms Multi-modal perception techniques (e.g., vision, tactile, force) Machine learning models for physical behavior prediction and manipulation strategy adaptation Real-world
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areas is expected: numerical analysis, scientific computing, model reduction, uncertainty quantification, machine learning, fluid mechanics. Experience with scientific object-oriented programming
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at the University of Tübingen that investigates individual, social, and institutional determinants of learning and educational processes. We employ a wide range of methodological approaches, from large-scale
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. Furthermore, we develop advanced scattering methods and machine learning tools for data analysis. For more information, see www.soft-matter.uni-tuebingen.de Qualification and skills Candidates should have good
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-scale controllable, and cost-efficient disease models by bringing together experts in physical chemistry, physics, bioengineering, molecular systems engineering, machine learning, biomedicine, and disease
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Researcher / Postdoc for molecular investigations on microbial ecology in deep-sea polymetallic n...
Qualifications and Skills Knowledge of microbial metabolic processes and methods to study them (e.g., tracer-based incubations) and general marine/benthic biogeochemistry Interest and intention to acquire and
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to improve or maintain their German language skills and learn from each other. Your application To apply, please submit your application including a letter of motivation, CV and contact details of two
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student assistants and contribute to shaping the CRC’s research direction Your Profile PhD in computer science, neuroscience, machine learning, or related field Strong programming skills in Python and
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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | about 2 months ago
and free in-house language courses The group language is English, so no German language skills are required – but it is a great opportunity for you to learn German! The historic city of Göttingen
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or a related discipline A solid background in climate and atmospheric sciences, and extreme weather ideally supported by knowledge of machine learning and time series analysis is of advantage, as is