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Field
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neurostimulation (TMS, tDCS, etc.), neuroimaging (EEG, MRI, MEG, etc.), or multi-modal neurostimulation-neuroimaging techniques. Machine learning background and/or knowledge. Experience working with individuals with
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to effectively learn this technique will be needed. Effective oral and written communication skills. Must be computer literate with proficiency and working knowledge of database and reporting tools such as
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Computer Science Department at Princeton University. We seek candidates with computational biology, bioinformatics, computer science, machine learning, statistics, data science, applied math and/or other
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to collaborate with other researchers, and mentor graduate and undergraduate students, and may also teach one course per year for the Department of Statistics. A Ph.D. in Statistics, Biostatistics, Machine
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research on how engineers learn, how engineering knowledge and identities are formed, how we assess and evaluate learning, and how educational systems can be designed and transformed to support meaningful
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modeling and risk assessment, and demonstrated experience in one or several of the following areas: Tropical cyclone dynamics and thermodynamics Statistical and/or machine learning approaches to weather
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engagement efforts contribute to robust learning and working environments for all students, staff, and faculty. We invite individuals who will join us in our mission to improve health equity and well-being
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) Cleaning and managing large datasets from administrative data sources or online learning platforms Causal machine learning (e.g., double/debiased machine learning (DML), causal forests, generic ML) Learning
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applications for a Postdoctoral Scholar, Instruction position for the Fall 2026 semester. The selected candidate will teach at the undergraduate level, including general chemistry, along with supervision
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field Computer Skills General office suite and willingness to learn lab specific programs Strong programming skills in R and/or Python Experience with Next Generation sequencing Record of peer-reviewed