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Brandenburg University of Technology Cottbus-Senftenberg • | Cottbus, Brandenburg | Germany | 2 days ago
(computer-based), or 79 points (Internet-based) Cambridge Advanced English test (minimum grade B) Cambridge Certificate of Proficiency (minimum grade C) IELTS Academic (minimum 6.5) Application deadline
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academic and industrial cooperation partners Requirements: excellent university degree (M.Sc., Diploma) in either computer engineering, computer science, electrical engineering or any related natural science
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services Teaching / training abroad (Erasmus+) Back Erasmus+ within Europe Erasmus+ worldwide Information for Back Prospective Students Current Students Staff Back Advice and help Computer and IT Staying
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: A completed university degree (Master or equivalent) in computer science, data science, applied mathematics, physics, materials science, or a related field Prior experience in computer vision, deep
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implementation on IBM’s ibm_cleveland quantum computer by reproducing recently published benchmark QM/MM simulations [2] Apply the developed code to simulate proton transport in vesicular glutamate transporters
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developing and using dedicated tools and processors Contribute to our sparse auto-differentiation libraries to accelerate the training of state-space models Collaborate closely with our internal partners
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ties with the local experimental groups of TUD and the institutes of the DRESDEN-concept environment. The chair hosts its own computer cluster and has full access to the high-performance computing
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equivalent) in computer science, data science, applied mathematics, physics, materials science, or a related field Prior experience in computer vision, deep learning, or signal processing; familiarity with
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literacy and basic programming skills (R, Python), or the willingness to develop these skills Analytical mindset, with a keen interest in advancing proteomic methodologies We offer Cutting-edge proteomic
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/biomedical engineering or of relevant scientific field A solid background in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning packages