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graduate student at the University of Michigan Available to attend lectures and lead lab sessions Demonstrated knowledge and skill in Python, including libraries and methods relevant to scientific computing
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analysis of images or volumes, e.g., in ImageJ, or Python. Experience in visualization software, e.g., Blender, DragonFly. Knowledgeable in programming, e.g., Python. High motivation, ability to quickly
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will require a strong interest in experimentation, reproducibility of results, and reading scientific papers. Good programming skills (in practice Python) are expected, as well as a genuine interest in
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their results in the context of the clients. Analyses will be conducted with several software packages for statistical data analysis (possibly including R, SAS, Python, …). The new colleague may acquire new
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referencia. Habilidades de programación en Python y plataformas de aprendizaje profundo como PyTorch. Habilidades de comunicación oral y escrita en inglés. PhD degree in computer science, electrical
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/Qualifications Experience with molecular simulations (LAMMPS, GROMACS or equivalent) and/or electrostatics simulations (APBS or equivalent). Strong programming skills (Python, FORTRAN, C, or similar). Experience
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the consortium Your Profile: Excellent Master and subsequent PhD in computer science, engineering, biophysics, applied mathematics, computational biology or a related field Proven programming expertise in Python
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methods for calculating breast cancer screening rates across two systems. They should have advanced expertise in SQL and have experience using statistical or programming packages like R or Python
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. Main tasks Study the existing Matlab code and understand the underlying MCR-ALS workflow Translate and implement the method in Python in a way that is compatible with SasView Investigate how the new
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for QMSS (including which course(s), if applicable) and the skills (e.g., analytical tools such as Excel, R, Tableau, Python, etc.) and experiences (e.g., jobs, internships, research, coursework, teaching