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of machine learning or quantum computing Programming skills in Python and/or C/C++ Experience with scientific software tools and numerical libraries Familiarity with Linux-based computing environments Ability
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skills. Is confident using digital learning tools such as Python, SAS, Stata or similar. Holds (or will soon complete) a doctorate in Finance or a closely related field. Enjoys contributing to the wider
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. Practical experience applying machine learning or deep learning methods to biological data. Proficient in Python, with working knowledge of bash and experience using HPC or cluster environments (e.g. SLURM
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dissemination through scientific conferences (oral presentations/posters), peer-reviewed journals and outreach. Where to apply Website https://calls.bcbl.eu Requirements Research FieldTechnology
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members and collaborators. For additional information about the Liao research group, please visit: https://sites.google.com/view/chentingliao/ Department Contact for Questions: Questions regarding
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(e.g., Python, MATLAB) Practical experience with laser optics, vacuum technology, cryogenics, and FEM simulations is highly desirable Proactive working style with high level of commitment in solving
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for measurement data (preferred for plasma physics or HEP). Knowledge of Python, Matlab. Additional assets: Experience in laboratory work and knowledge of the principles of particle detectors and measurement
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presentations and draft sections of research papers Location: Department of Economics, Harvard University, Cambridge, MA Supervisor: Professor Gita Gopinath, website: https://gopinath.scholars.harvard.edu