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Field
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imaging phantom-based evaluation of quantitative SPECT/CT; reconstruction algorithm development; establishing a secondary standards laboratory for unsealed source metrology through gamma spectrometry
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at the Computational Imaging Research Lab (CIR) and the Department of Cardiology at the Medical University of Vienna and the Visualization and Data Analysis Research Group (VDA) at the University of Vienna. Your Tasks
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advanced statistical machine learning, reinforcement learning, and gen-AI-driven decision models for supply chain and operations optimization. • Design scalable algorithms for demand forecasting, risk
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tools. * Familiarity with tensorflow and/or pytorch. * Demonstrated ability to design and implement machine learning techniques and algorithms. * Demonstrated expertise in the Linux computing environment
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neurophysiological recordings, imaging studies, and behavioral experiments Present research findings at internal seminars, external conferences, and scientific meetings Actively engage in the Neuroscience PhD Program
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gained as an undergraduate); strong quantitative background and computer skills including programming experience; excellent academic record; and ability to work independently. PREFERRED: Research assistant
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Diseases. Reporting to the Section Chair, the Data Science – CDM faculty are expected to develop, sustain, and lead an active, obvious, externally funded research program with outstanding scholarship and to
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computational models of the immune response for multi-scale epidemic models. This position offers an excellent opportunity for recent graduates interested in applying quantitative and computational methods
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Description We are seeking a motivated new PhD candidate who wants to join an exciting collaborative research program within the VIB-Center for Inflammation Research between the Guilliams and
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on MMS data. Required Knowledge, Skills & Abilities: Computer analysis of digital data from satellite data centers. Physics background analyzing the data. Other Requirements: local residency. Preferred