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challenging, and new theoretical methods and algorithms are required. The research project aims at deriving priors for Bayesian methods from atomistic simulations and machine learning. It also offers
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Infrastructures Didactics of Informatics Digital Humanities Distributed Systems High-Performance Storage Machine Learning Medical Informatics Neural Data Science Practical Informatics Scientific Information
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Machine learning Experience is ideally shown through a thesis, seminar papers, or scientific publications. Alternatively, excellent grades in a respective Master’s programme. Strong intrinsic motivation
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of embedded machine learning, neuromorphic hardware and deep learning accelerators. Want to get more information? Click here. What you will do Design innovative memory arrays for non-volatile memories Develop
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of embedded machine learning, neuromorphic hardware and deep learning accelerators. Want to get more information? Click here. What you will do Responsible for writing Verilog/ VHDL code for AI blocks Perform
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September. Online registration is required prior to application: https://mpimet.mpg.de/en/career/imprs-esm . Tuition fees per semester in EUR None Combined Master's degree / PhD programme No Joint degree
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Your Job: In this position, you will be an active part of our Simulation and Data Lab for Applied Machine Learning. Within national and European projects, you will drive the development of cutting
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organisation To achieve valuable scientific results, talented PhD students need to acquire knowledge and are also required to exchange knowledge and experience with other PhD students in method-oriented working
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information science techniques. Several areas of computer science and mathematics play important roles: data management and engineering, machine learning and data analytics, signal and image processing
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of methodologies, from in-depth behavioral assessments to computer vision, machine learning and neuroimaging techniques, we aim to uncover the complexites of neurodevelopmental disorders. Our