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algorithms, computational complexity theory, and information theory Relevant coursework and experience in spiking neural networks, and statistics A strong electronics background, including experience in
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personalized psychiatry, network science, and recovery-oriented research; Interest in integrating neural, behavioral, and recovery-related outcomes; Excellent communication skills and the ability to work in
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analysis) to compare brain responses with predictions of computational models (deep neural networks developed by the NASCE team). The objectives include assessing how the brain segments, groups
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in C++ and/or Python is expected, and experience in model analysis and parameter optimisation is beneficial. Experience in machine learning and neural networks is desirable. The successful applicant
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SAF combustion. Recent advances have demonstrated that machine learning techniques, particularly neural networks, can significantly accelerate chemical kinetics computations. Nevertheless, most of
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, segmentation), physics-informed neural networks, and having worked with large datasets are assets. An innovative spirit and team player skills round off your profile. We offer We are a dynamic and international
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, computer science, applied mathematics, physics or a similar area - very good programming skills in Python - good prior experience with neural networks using common Python-ML libraries such as PyTorch
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implementations (e.g., biophysical models), as well as models of machine intelligence (e.g., deep convolutional neural networks). We test the models' predictions in our empirical studies with human participants
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science, applied mathematics, physics or a similar area very good programming skills in Python good prior experience with neural networks using common Python-ML libraries such as PyTorch preferably also background
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 7 days ago
the Fugger lab at the Oxford Centre of Neuroinflammation , focusing on the development of drugs that tame common brain diseases through the application of graph-based neural networks, deep learning, and