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programming languages (e.g., Python, MATLAB, R) for complex data analysis Excellent written and verbal communication skills Ability to work both independently and collaboratively in a research setting Preferred
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and other machine learning models (especially neural network models, time-series models) and coding in python and R. Strong collaborative skills and ability to work well in a complex, multidisciplinary
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or MD/PhD Strong programming skills, preferably in R and/or Python Previous expertise and/or interest in single-cell sequencing technologies, bioinformatics, spatial analyses, and generative AI is desired
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mechanisms of neuromodulation. Discover mechanisms how diverse ligands targeting GPCRs or diverse receptors elicit distinct phenotypic responses. Relevant publications Lobingier B and Hüttenhain R, et al
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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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or gene editing by CRISPR-Cas9 is required. Experience with flow cytometry and/or mass cytometry analysis is desirable. Interest in learning new technologies is mandatory. Basic R programming skills
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an individual with strong statistical and computing backgrounds. Successful applicants should have a Ph.D. degree in epidemiology (or biostatistics or a related field). Strong programming skills in R are required
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model APIs, cloud computing environments, and R for additional statistical analysis. For decision support prototype development and evaluation, web-based user interface design, human-computer interaction
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latent variable models (especially factor analysis, item response theory, and growth modeling) and coding in R. Strong collaborative skills and ability to work well in a complex, multidisciplinary
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Expertise and hands-on experience using LLMs, Machine Learning, Deep Learning frameworks, Natural Language Processing, etc. Proficient programming skills in Python and R and working knowledge in SQL Strong