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excellence and values innovation, collaboration, and life-long learning. To foster the talents and aspirations of our staff, Stanford offers career development programs, competitive pay that reflects market
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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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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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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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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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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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and advanced attendees Schedule Flexibility with work schedule Compensation Grade LOA https://www.unr.edu/hr/compensation-evaluation/salary-schedules/loa-and-postdoc Exempt Yes Full-Time Equivalent 0.0
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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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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
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University community. Please visit their website to learn more. Special Instructions to Applicants provide 3 references Quick Link for Internal Postings https://www.auemployment.com/postings/44281