57 machine-learning "https:" "https:" "https:" "https:" "https:" "The Francis Crick Institute" PhD positions at Forschungszentrum Jülich
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diffraction data where the information extends towards 3-d space. Machine learning offers promising approaches for the solution of complex problems of disorder, ultimately aiming at general and automated
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: Investigate and design optimal computing and communication architectures for hardware acceleration of large-scale machine learning workloads Perform characterization and modeling of electronic and optical
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acceleration of large-scale machine learning workloads Perform characterization and modeling of electronic and optical devices Develop hardware-aware machine learning models incorporating electronic and optical
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research. You will strengthen the data science and machine learning activities of IAS-9 by developing core AI methods with applications to electron microscopy and materials discovery. You will work in a team
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, and training methods - across multiple technological platforms - photonics, electronics, biological neurons. Responsibilities and tasks This PhD project aims to develop, verify, and benchmark learning
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Your Job: Modeling and characterization at molecular level of selected biological processes by performing classical molecular dynamics, and employing enhanced sampling methods and machine learning
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neurons. Responsibilities and tasks This PhD project aims to develop, verify, and benchmark learning rules in networks of complex spiking neuron models in the application field of geolocalization: Building
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NEST: https://nest-simulator.readthedocs.io Your tasks in detail: Work with the NEST main code base and experimental branches Dissect the spiking network simulation cycle into phases and capture the flow
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, motivation to learn new skills to expand scientific knowledge Excellent communication skills and ability to work in an interdisciplinary team Very good written and oral communication skills in English (at
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the following areas desirable but not essential: electrocatalysis, rheology, coating technology, machine learning Intrinsic motivation to show initiative, creativity, and to work independently Excellent