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Mechanical Engineering or Materials Science and Engineering (required for Ph.D. applicants) Experience with additive manufacturing, materials characterization, and/or physics-informed machine learning
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comparative genomics, chromatin architecture, gene expression, protein abundance, and metabolite profiling—combined with computational biology, machine learning, and advanced statistical methods. Supported by
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refractive-index imaging of complex samples. Apply machine learning and deep learning techniques to automate segmentation and quantitative analysis of tomographic refractive-index data from cells and tissue
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well as innovative and inquiry-based teaching and learning. The Faculty consists of six departments as well as a Faculty administration. Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/296312/phd
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/Associate/Full Teaching Professor (a non-Tenure-Track faculty position) in Miami with general areas of focus in Application Engineering & Development, Artificial Intelligence/Machine Learning platforms
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machine learning and computer simulations. The focus of the PhD project will lie on developing machine learning models for clustering, classification, regression and reinforcement tasks to work with
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. Skills in computational modelling or machine learning applied to brain signals are an asset. We are looking for a highly motivated, rigorous and curious researcher who is ready to invest themselves in a
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following criteria: PhD in Computer Engineering, Computer Science, Electrical Engineering, or a closely related field Demonstrated research excellence, evidenced by peer-reviewed publications Expertise in
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development, artificial intelligence, computer simulations, programming and programming languages, ethics of technology, service learning, and integration of Christian faith and scholarship. Core attributes we
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cutting-edge knowledge. Required Qualifications & Experience PhD in a relevant field, including Biophysics, Cell Biology, Neuroscience, Cancer Biology, Biomedical Engineering, Bioengineering, or related