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Your Job: Reinforcement Learning (RL) is a versatile and powerful tool for control, but often data-inefficient, requiring numerous updates and non-local information such as replay buffers and batch
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biological, biotechnological and agricultural systems. The main focus is on machine learning approaches, in particular statistical learning, reinforcement learning, deep learning, and computer vision, as
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Ph.D. or equivalent degree in mathematics, physics, computer science, bioinformatics, or a related field Experience in developing deep learning models Ideally, prior experience in analyzing biological
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degree (or equivalent) in Data Science, Computational Biology, Bioinformatics, Computer Science, Physics or a related field Solid programming skills and knowledge in deep learning, statistical modelling
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, technology-driven start-ups. To do this, we rely on talents like YOU – with a mix of deep tech projects, financial support, professional premises, and a strong network of mentors and coaches. Become part of
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analysis, search and recommendation of music data. The main areas of responsibility include the following: implementation/porting of algorithms from the fields of deep learning and audio signal processing
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analysis, search and recommendation of music data. The main areas of responsibility include the following: implementation/porting of algorithms from the fields of deep learning and audio signal processing
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learning models Implementation of deep learning Improvement of models, e.g. in terms of efficiency, training performance or inference behavior What you bring to the table Enrolled Bachelor's/Master's student
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learning and data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms
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-the-loop AO for high-power lasers Turbulence-resilient free-space optical communications systems Wavefront sensors based on deep learning Development and construction of new wavefront sensors You will write