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Your Job: We are looking for a PhD student to contribute to the development of fast, accurate, and physics-informed machine learning models for predicting blood flow in patient-specific vascular
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. This PhD position focuses on the design of novel computer architectures to enable large AI models to run on embedded and edge systems under strict timing, energy, and memory constraints. Current solutions
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University of Massachusetts Medical School | Worcester, Massachusetts | United States | about 2 hours ago
-sequencing technologies and mouse disease models is advantageous but not required. Applicants should send a letter (via email) describing their current research activities and their interest in this position
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, affinity chromatography, immunoblotting, immunohistochemistry, flow cytometry (FACS), experimental glioblastoma models, work with laboratory animals, mass spectrometry and bioinformatics analysis methods
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Current Employees: If you are a current Staff, Faculty or Temporary employee at the University of Miami, please click here to log in to Workday to use the internal application process. To learn how
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design (TCAD) tools should operate at the ab-initio and quantum mechanical level. Moreover, they should capture the interplay between electrical (voltage-induced currents), thermal (excitation of crystal
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models (DDM, sequential sampling, Bayesian models). Experience with computer vision tools (e.g., MediaPipe, OpenPose, homography estimation, optical flow). Experience with eye-tracking data collection
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hydrodynamic coastal flow fields using SWAN, SWASH, SCHISM or a comparable model; writing python code to advect virtual macroplastic items in these flow fields using the Parcels-code.org framework; exploring
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an above-average PhD in energy system modeling, material flow analysis, or a related field, and a corresponding master`s degree You have extensive experience in industrial ecology and material flow
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of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, to commence on 01.04.26. Information on the department can be found at: https://bmi.ku.dk/english/about_department