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electrophysiology data obtained through collaborations and perform cross-species comparisons. We use machine learning techniques for neural data analysis and computational modelling with a special interest in
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the neurovascular space. Knowledge of neurovascular anatomy, acute stroke, endovascular treatments, neuroendovascular devices for the treatment of stroke. Ability to generate machine learning analysis of medical
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AI / Machine learning / Computational Oncology lab:Our work is translationally focused, towards realizing our vision of developing new approaches for fast and low-cost prediction of patient response
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their appointment. PhD in Nutritional Studies, Nutritional Epidemiology, Public Health, or a related field. Strong background in research methods, including intervention studies and/or clinical trials. Experience
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Department Name 81080:ENTOMOLOGY Work Location Lexington, KY Type of Position Faculty Position Time Status Full-Time Tenure Track Status Tenure Track Required Education PhD in Entomology or a related
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the period of the project, not exceeding the maximum period set by FCT for such grants. RENEWALL Renewable is subject to performance if the candidate is enrolled in a PhD program - art. 6º, n.4 c) https
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Simulation – Data Analytics and Machine Learning (IAS-8) at Forschungszentrum Jülich, which is dedicated to pushing the boundaries of data science theory and application. Our research spans from use-inspired
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data at an internationally competitive level. Experience of biostatistics or machine learning approaches Proficiency in a scripting language like R or Python, as well as ability to work efficiently in a
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-cell transcriptomics, or spatial tissue profiling data, and are keen to develop new methods, for example using machine learning. You have a proven track record of independent research funding and high
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on the problem of making distributed machine learning robust to network outages and computational bottlenecks. The work is part of the Norwegian national AI centre SURE-AI, and the PhD student will