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Job related to staff position within a Research Infrastructure? No Offer Description Project description Third-cycle subject: Computer Science PhD students will work on robot learning for manipulation
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, DeepFields (using drones, airborne optical sectioning (AOS) -a unique synthetic aperture sensing technique developed by JKU-, and machine learning for harvest and damage estimation in agriculture), in
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/job/295231/phd-research-fellow-in-machine-learning-and-statistics Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/295231/phd-research-fellow-in-ma… Requirements Research
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of machine learning to the practical tools of deep learning, now available through modern foundation models. For the theory part, the selected candidate will work in close collaboration with
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statistical mechanics. The Computational Biochemistry group consists currently of eight coworkers and combines quantum chemistry, statistical mechanics and machine learning with biochemistry, medicinal
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‑mining and machine‑learning methods. The expected scientific outcome is to establish guidelines for identifying and optimizing promising electrolyte materials and to support the development of future
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data management and machine learning is also preferred. An interest in energy system topics such as the green transition, sustainable energy systems, digital energetics etc. is preferred. Experience
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-oriented background - You have a genuine interest in signal processing and machine learning methodology and algorithms - You obtained good grades in courses related to the topics relevant to this PhD
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. Familiarity with frameworks such as TensorFlow and Keras, as well as libraries including Scikit-learn, NumPy, and pandas; - Experience with machine learning models such as Extreme Learning Machine (ELM
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stochastic modeling, Bayesian inference, data fusion and modern machine learning. Its research activities span various application domains such as security, non-destructive testing, infrared imaging and