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1,000 employees from over 50 nations, it is the largest institute of the Max Planck Society . The Department of Theoretical and Computational Biophysics headed by (Prof. Dr. Helmut Grubmüller) is
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, Information Science, Data Science and Artificial Intelligence. We employ over 200 people in four divisions: Artificial Intelligence & Data Science, Algorithms, Interaction, and Software. The atmosphere is collegial and
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. You will work under the supervision of Prof. Francisco C. Pereira, Assoc. Prof. Carlos Lima Azevedo (DTU), Dr. Biagio Ciuffo and Dr. Georgios Fontaras (JRC). You will work on research focused
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environment-specific algorithms and machine learning approaches. At the end of the project a technology demonstrator will be built using UAV- and USV- mounted radar sensors, and it will be tested in real world
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motors and braking technology, high-torque density axial flux electrical motors, development of servo controllers and algorithms, and special electrical machines such as superconducting electrical motors
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performance and future potential. The successful candidate will work under the main supervision of Prof. Holger Voos and will be required to perform the following tasks: Carry out the aforementioned research
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approach could resolve this issue and we could use obtain data-driven models using machine learning algorithms such as artificial neural networks, reinforcement learning, and deep learning. A typical caveat
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models through specific activation functions. This project will be undertaken in collaboration with Dr Hemanth Saratchandran and Prof Simon Lucey of the Australian Institute for Machine Learning, and
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The candidate will be embedded in the Theory cluster at the Leiden Institute of Advanced Computer Science, supervised by Dr. Tobias Kappè and Prof. Dr. Marcello Bonsangue from the System Modelling and Analysis
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involves the use of quantum chemistry, machine learning, and genetic algorithms to search for new homogeneous chemical catalysts. Who are we looking for? We are looking for candidates within the field