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SPECIFICS The Penn State College of Medicine, Cancer Institute in Hershey, PA is seeking a Postdoctoral Scholar to join an NIH-funded prestigious Program Project focused on acute myeloid leukemia (AML
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of head and neck squamous cell carcinoma (HNSCC). The overarching goal of the research program is to identify biologic determinants of tumor control and normal tissue injury following radiation therapy, and
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intentions and career plan. This document must be composed of three sections: 3.1) Background: Expertise and skills gained. 3.2) Research Interests: Research intentions and goals for the postdoctoral role and
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each stage of CKMD diagnosis. Candidates for this position should have experience in the areas of public health, epidemiology, and statistics. Experience in statistical programming (R, Unix, Linux, etc
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executing aspects of our SNAP Ed and community-based nutrition education programming. This includes providing in person or zoom based nutrition education, food tastings, and cooking demonstrations to diverse
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students, assisting them in their research programs. This position offers an opportunity to gain hands-on experience, contribute to cutting-edge projects, and develop essential technical skills. Students
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, Computer Science, or a related field. Basic understanding of Python programming. Familiarity with natural language processing concepts is a plus. Strong analytical and problem-solving skills. Ability to work
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learning, bioinformatics methods in -omics data are preferred. Demonstrated evidence of excellent programming, collaboration, and communication skills. Responsibilities: As a Postdoctoral Scholar, you will
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. Applicants should have a JD or LLM degree or be in a program pursuing a JD or LLM degree. BACKGROUND CHECKS/CLEARANCES Employment with the University will require successful completion of background check(s
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. Programming skills (Python etc.) required and interest in learning about data and algorithmic privacy Requirements, qualifications, and/or competencies: Must apply with a CV and it is for a project in data