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energy use more efficient. We develop new optimization methods, machine learning algorithms, and prototypical energy management systems (EMS) controlling complex energy systems like buildings, electricity
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the European Marie Sklodowska-Curie Training Network programme FADOS. The successful candidate will join a cohort of 17 Doctoral students distributed over 16 research groups in Europe and the UK. About FADOS
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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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Your Job: Agile development, maintenance, coordination, testing, distribution and deployment of the open-source, community-driven Elephant neural data analysis software - https://python-elephant.org
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, machine learning algorithms, and prototypical energy management systems (EMS) controlling complex energy systems like buildings, electricity distribution grids and thermal energy systems for a sustainable
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, machine learning algorithms, and prototypical energy management systems (EMS) controlling complex energy systems like buildings, electricity distribution grids and thermal energy systems for a sustainable
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, machine learning algorithms, and prototypical energy management systems (EMS) controlling complex energy systems like buildings, electricity distribution grids and thermal energy systems for a sustainable
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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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energy use more efficient. We develop new optimization methods, machine learning algorithms, and prototypical systems controlling complex energy systems like electric grids and thermal systems for a
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13.01.2020, Wissenschaftliches Personal PhD position at the Chair of Algorithms and Complexity. Candidate shall work on approximation algorithms for scheduling problems in parallel and distributed