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physiological sensing systems (e.g., PPG, ECG, EOG, ...) bonus: ML-based signal processing (deep learning on time series) Application documents to be submitted a PDF showing your projects that are most relevant
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projects or employment). Your profile You have outstanding experience in Machine Learning with a PhD degree from a university in Computer Science, or related fields, with a proven track record in machine
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experiments workflows in areas such as simulation, classification, or anomaly detection using machine learning and deep learning methods, exploring, in particular the performance of Quantum Computing
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-edge topics, and services of high practical relevance. We are seeking someone to join our research team with immediate effect or by mutual agreement: PhD Candidate Distributed Information Systems in
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characterisation of diagnostic and therapeutic tracers Tumour imaging, clinical oncology and data analysis Semiconductor detectors, nuclear physics and Monte Carlo simulation Machine learning, deep learning and
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). The PhD dissertation project will focus on how to experimentally capture hypothetical ductus (stroke order and direction of writing) reconstructed by experts and to design deep learning pipelines as
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stakeholders, and will contribute to the successful completion of the above-mentioned scope. List of the main tasks: Acquire a deep understanding of the scope of the project and of CERN's electrical network
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Skills and/or knowledge A highly motivated Software Engineer eager to learn and grow in a collaborative and supportive environment; Proficiency in Python programming language, with a solid understanding of
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is a plus Requirements Additional Information Website for additional job details https://www.hipeac.net/jobs/14573/phd-position-on-secure-machine-learning-on-ri… Work Location(s) Number of offers
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pollution research Skills in a relevant programming language (e.g., R, Python) are essential, ideally including machine/deep learning and natural language processing Practical experience or good familiarity