30 software-formal-method-phd Postdoctoral research jobs at Technical University of Munich in Germany
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these changes, identify their causes and describe their impacts on biodiversity and ecosystem services. To do this we use a combination of diverse methods, from empirical research to remote sensing and simulation
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machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods, machine learning algorithms, and
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CW and femtosecond optical spectroscopy methods. Preference will be given to candidates who already have some postdoctoral experience, but applications from recently graduated PhDs with an excellent
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us We are TUM’s unique Pathology AI lab developing new machine learning (ML) methods for automatically analyzing digital pathology data and related medical data. Such methods include the automatic
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representation theory. • Some experience with SageMath, polymake or other related mathematical software. • Proficiency in English, both written and spoken. Knowledge of German is not required. In addition
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” are ready to be exploited. • You will also be involved in the training of students. Your qualifications and skills: • You have a PhD or equivalent degree in biology, agri-cultural biology or any related field
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, structure theory of Kac-Moody algebras, geometric/combinatorial representation theory, quiver representation theory. • Some experience with SageMath, polymake or other related mathematical software
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methods, machine learning algorithms, and prototypical systems controlling complex energy systems like buildings, electricity distribution grids and thermal systems for a sustainable future. These systems
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skills further, there is also the opportunity to aid in the planning, organization, and running of lectures. Required training, skills, and background • PhD degree in bio/medical engineering, materials
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of healthcare, science, technology, society, and the environment. Our mission encompasses both theoretical and empirical methods to foster ethical, transparent, and interdisciplinary research, education and