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for publication. Preferred qualifications: Experience with super-resolution microscopy, coding (Phyton, Matlab), and machine learning is preferred. City of Hope employees pay is based on the following criteria
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. Ideal candidates will have demonstrably strong research skills, evidenced by multiple publications in top-tier machine learning or artificial intelligence conferences and/or leading scientific journals
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. transformer models). One focus of this work will be on B-cell receptor evolution. Experience in applications of modern machine learning methods as well as in biological data analysis are needed for the position
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systems using computer vision, quantitative image analysis, deep learning methods for detection, diagnosis, and quantitative analysis of abnormalities with multimodal data, including clinical and
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have a PhD in physics, biology, or a related field by the time of appointment. The ideal candidate will also have demonstrated experience in machine learning and biological data analysis and a strong
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reproducible analysis workflows Familiarity with computational models of vision and machine learning methods (for example CNNs, deep generative models, encoding models) is preferred but not required Ability
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computational models of vision and machine learning methods (for example CNNs, deep generative models, encoding models) is preferred but not required Ability to communicate scientific results clearly through
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quantum chemistry, experience with machine learning regression methods. Preferred start date as soon as possible but flexible. Basic Qualifications PhD in Physics, Chemistry, Materials Science, Computer
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focusing on multi-omic integration analytics, machine learning, and/or AI. In addition to carrying out research, the successful candidate will be expected to apply for fellowship funding, contribute
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· Communicate project progress and coordinate with research team Duration: · 3 ½ months Preferred start date as soon as possible but flexible. Basic Qualifications: · PhD or equivalent in engineering, building