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computing, obtained within a maximum of 7 years; application of machine learning and deep learning methods to remote sensing images; proficiency in programming (R, Python, or similar); ability to work
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learning or a related field experience in the development of machine learning models using Python and pytorch expertise in two or more of the following technical areas: implementation of signal processing
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proteins Do ligand docking and pocket design Design and filter in silico libraries at scale Write strong Python and are comfortable with structural-biology tooling Can own a design campaign end to end, and
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collection procedures. Data Processing Execute and monitor established data workflows, including running existing Python, R, SQL, and other automated scripts that support recurring data projects. Process
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collaboratively in an international research environment Preferred qualifications: Proficiency with a relevant data-analysis environment, preferably Python or R, and SPSS Background in comparative higher education
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related to modeling and simulation of biological systems, 3) very good IT skills, in particular the ability to program in Python, 4) very good knowledge of machine learning methods, neural networks, and
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analyze multi-omic data provided by our collaborative partners and interpret the results from a biologically relevant perspective. Planned activities include Python code development, the analysis and
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, with possibility to extend Appointment Start Date: Flexible (rolling review of applications) Group or Departmental Website: http://pollacklab.stanford.edu(link is external) How to Submit Application
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of a Microbial Planet” (https://ccomp-stc.org/ ) as well as a new collaboration with researchers in the Mathematics Department at Toronto Metropolitan University (TMU). The goal of this project is to use
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Professional 1: Prior experience in rodent behavioral research lab or similar; Knowledge of neuroanatomy and/or animal behavior; Experience with coding, especially in Python or Matlab Essential Qualifications