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and/or spatial genomics datasets is a plus but not necessary. Proficiency in programming (e.g., Python, R) and familiarity with common bioinformatics tools and packages. A PhD in developmental biology
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postdoctoral candidate has an MD and/or PhD in neuroscience or related field and extensive experience with rodent neuroscience. Excellent analytical skills, e.g., Python & Matlab, are strongly preferred, as is
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GIS software and Python, strong written and interpersonal communication skills, and a demonstrated interest in addressing social justice issues through data-driven research. The postdoc will work in
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skills and demonstrated ability to complete detailed work accurately. Programming experience in R, Python, Stata, SAS, and/or other languages Prior research experience and coursework in the empirical
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/Python coding, next-generation sequencing data interpretation, large-scale data integration, and machine learning. Science: strengthen the ability to formulate hypotheses, design aims to test the
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sequence programming (ex: Pulseq) Python, MatLab, C++, etc PyTorch, TensorFlow ML Ops Required Qualifications: MD, PhD, or equivalent Technical interest & expertise in MRI Required Application Materials: CV
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working with large healthcare datasets (EHRs, claims, registries). Proficiency in R or Python. Strong quantitative skills and familiarity with advanced modeling techniques. Excellent written and verbal
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technical skills in statistics, data science and psychometrics Experience with open-source software development (or high proficiency) in R or Python Domain knowledge in reading development, dyslexia research
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software (e.g., WaterTAP) and programming languages (e.g., Python) is highly desirable. Familiarity with the principles of electrified mineral extraction and purification processes is advantageous but not
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paradigms in primates or humans – Theoretical neuroscience, machine learning, or AI • Proficiency in Python, MATLAB, or equivalent data‑analysis frameworks. • A passion for big‑picture questions, open science