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, progression, and therapeutic response. This research is fundamental to advancing our knowledge of cancer and improving patient outcomes. See further information at the lab webpage: https://odin.mdacc.tmc.edu
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Requirements: PhD in Biomedical Engineering, Electrical Engineering, Neuroscience, Computer Science, Psychology, or closely related field Demonstrated MEG analysis experience (FieldTrip/Brainstorm/MNE-Python
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. Program in Python. Analysis of quantitative data. Write technical documents / reports. Read scientific papers, journal articles, and (astro)physics textbooks. Participate in weekly research meetings
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modeling with SUMO. Programming transport modes with Python. Integration of climate constraints into a transport model. Emergency and disruption management. Where to apply Website https://sede.uvigo.gal
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robots for facade operations. Programming in MatLAB and Python. Navigation in GNSS-denied environments. Publicacion of scientific papers. Development of project deliverables. Where to apply Website https
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
/Description: The Miao Lab in the Computational Medicine Program and Department of Pharmacology at the University of North Carolina – Chapel Hill (https://www.med.unc.edu/pharm/directory/yinglong-miao/) is
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-led lectures. This is a limited availability position* Employment fraction: 0.50 Course Description COMPFOR 221 (Digital Media with Python): "COMPFOR 221 is an introduction to digital manipulation and
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). Develop robust, reproducible and reusable Python code for model training, inference, and large‑scale computational experiments. Run and manage high‑throughput workloads on HPC or cloud infrastructure
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Knowledge in the field of Machine Learning, including training, inference, and optimisation of transformer architectures. Knowledge in the field of ML security is desirable. Good Python skills, especially
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Python programming skills are required, and prior experience with developing open-source software or databases will be considered a plus. Candidates should apply at: https://puwebp.princeton.edu/AcadHire