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. Expertise in computational neuroscience software (e.g., MATLAB, Python) as well as statistical methods and statistical packages (e.g. SAS, R). Experience with machine learning methods is preferred
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and machine learning based software to assist clinical workflow and pre-clinical studies. Recent software developed from the group has been adopted in the clinic and preclinic labs. The scientific
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, robust, and reproducible data analysis. Conventional statistical approaches will be combined with innovations in interpretable machine learning to address each aim from multiple angles. Analysis code will
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Posted on Fri, 04/19/2024 - 15:02 Important Info Faculty Sponsor (Last, First Name): DeBoer, Charles Stanford Departments and Centers: Ophthalmology Postdoc Appointment Term: 1 Year, possible
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. Develop and apply ab initio computations, molecular dynamics simulations, and machine learning models. Collaborate with other researchers within the group and external partners. Present research findings
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clinical shadowing experiences. Research topics range from machine learning, designing, and evaluating clinical decision support content to disintermediate scarce medical consultation resources, evaluating
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principals to problem solve work. ● Ability to maintain detailed records of experiments and outcomes. ● Ability to quickly learn and master computer programs, databases, and scientific applications
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, mathematics, physics, or a related field. The ideal candidate should demonstrate a record of publications in the area. Strong knowledge in machine learning, statistics and programming skills (R, Python
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. • Develop computational and theoretical models that bridge neural data and behaviour, leveraging modern machine‑learning toolkits. • Drive multi‑lab collaborations across SCENE; co‑author high‑impact
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the use of R and/or Python Basic understanding of statistical modeling, and machine learning Understanding of high-throughput sequencing techniques including whole genome, whole exome, targeted capture, RNA