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Field
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open for a minimum of 5 days after which it will close when a qualified candidate is identified and/or hired. We accept Word (.doc, .docx), Adobe (unsecured .pdf), Rich Text Format (.rtf), and HTML (.htm
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CV, including the contact address, work experience, and a list of publications At least one publication in full-text, authored by the candidate Early application is highly encouraged, as the
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Experience with machine learning, data mining and data assimilation is a plus Knowledge of git, docker, kubernetes, and/or metadata is a plus Ability to work within a team Excellent interpersonal and
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specific to mental health EHRs. The team conducts research using de-identified EHR data acquired through the Clinical Records Anonymisation and Text Extraction (CRATE) and Clinical Record Interactive Search
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for a duration of 9 months. To apply, please complete an online application and upload a plain text copy of your CV and covering letter only. In your covering letter, you should evidence how you meet or
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be asked to disclose any such participation at the time of hire for review by Brookhaven. The full text of the Order may be found at: https://www.directives.doe.gov/directives-documents/400-series
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moves. Success will be measured by having published or contributed to papers in top venues (e.g., Nature Science of Learning, Computers and Education, ACM Learning at Scale, Educational Data Mining) and
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Experience: Experience in advanced analytical theories, predictive modeling, data mining, and data extraction. Experience in clinical and health services research. Expertise in using various statistical
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identified and/or hired. We accept Word (.doc, .docx), Adobe (unsecured .pdf), Rich Text Format (.rtf), and HTML (.htm, .html) up to 5MB in size. Resumes from third party vendors will not be accepted
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candidate is identified and/or hired. We accept Word (.doc, .docx), Adobe (unsecured .pdf), Rich Text Format (.rtf), and HTML (.htm, .html) up to 5MB in size. Resumes from third party vendors will not be