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, engineering, physics, biophysics, applied mathematics, computational biology or a related quantitative field Strong background in deep learning for image analysis / computer vision, ideally on microscopy time
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physiology is an asset Experience in statistics and data analysis of large data sets (including time series analyses and machine learning) Good programming skills Very good communication and interpersonal
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assimilation, machine learning, and optimization techniques. Experience in student mentoring. Publications in leading journals within the field. Preferred Qualifications PhD in Environmental Modeling. More than
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to detail. Proactive and self-motivated mindset with an eagerness to learn and grow Excellent computer skills with demonstrated proficiency in Microsoft Office Suite. Please include a cover letter detailing
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responsibilities simultaneously. 3.Proficiency in Microsoft Office Suite, including Word, Excel, and Outlook, with the ability and willingness to learn new databases and computer applications. 4.Professionalism
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research staff, PhD students, or postdocs Providing guidance, training, and technical support to others in the research team Ensuring compliance with research ethics, safety regulations, and institutional
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data-driven methods relying on machine learning, artificial intelligence, or other computational techniques. The applicant is expected to develop and apply data-driven and machine learning-based methods
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develop methods to disentangle dynamic, multiscale ecological signals from large, heterogenous observational data. This work lies at the interface of statistics, machine learning/AI, ecology, and
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, and written communication skills evidenced by a publication record in the area of control theory, mathematical optimization, AI, or machine learning. Preferred Qualifications: Publication record in
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and resistance. Through close collaboration between laboratory and clinical teams, our work bridges mechanistic immunology with real-world patient outcomes. To learn more about Hosoya Lab - https