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. • Strong proficiency in Python and relevant libraries for data analysis and modelling (e.g., TensorFlow, Keras, Scikit-learn, Pandas); knowledge of R would be an asset. • Familiarity with geospatial data
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Engine. • Programming skills in Python or similar scientific computing environments, with experience in geospatial and machine learning libraries. SKILLS AND QUALITIES • Strong scientific rigor and
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the any of the following software: Matlab Python, other Preferred (not all): Knowledge and/or interest on control Experience in collaborative and international projects Experience/knowledge in HIL systems
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on cybersecurityl Knowledge and experience on advanced modelling Knowledge and experience with the any of the following software: Matlab Python, other Preferred (not all): Knowledge and/or interest on vulnerability
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Description Primary Duties & Responsibilities: A background on our research can be found by reading some of our recent papers at https://sites.wustl.edu/aminlab/ . Following instructions and discussions with
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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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architectures (e.g., convolutional neural networks or transformers); deep specialization is not required. Exposure to Generative AI concepts and large language models (LLMs) is a plus. Proficiency in Python
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technologies (such as HTML/CSS, JavaScript, Python, APIs, XML); and modern development workflows (such as Git, CLI, LTI). Must have the ability to understand and follow written and oral work instructions
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recrystallization and control nucleation for biomedical applications in e.g. heart and kidney cryopreservation. Where to apply Website https://www.academictransfer.com/en/jobs/359905/phd-in-de-novo-design-of-ice-bi
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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | about 8 hours ago
of classes, tutorial sessions, and teaching mode see the University of Toronto, Timetable Builder at: https://ttb.utoronto.ca/ . Faculty/Division: University of Toronto Mississauga. Department/Subject Area