59 molecular-modeling-or-molecular-dynamic-simulation Postdoctoral research jobs at Rutgers University
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experimental research on structural and functional characterization of Hybrid-Two-Component Systems (HTCSs) in Bacteroides. Uses molecular biology and molecular genetic techniques to engineer plasmids
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Investigator, the Postdoc(s) will be responsible for the design, analysis, interpretation and presentation of experiments regarding the study of molecular mechanisms of the regulation of synaptic transmission in
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savings options Employee and dependent educational benefits (when applicable) Life insurance coverage Employee discount programs Posting Summary The Aging & Brain Health Alliance in the Center for Molecular
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neurobehavioral assessments. Minimum Education and Experience: PhD or equivalent degree in neuroscience, neurobiology, molecular biology, biochemistry, psychology, genetics, pharmacology, or a related science field
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, molecular biology, or metabolic engineering with extensive computational research and lab experience. Certifications/Licenses Required Knowledge, Skills, and Abilities Preferred Qualifications A background in
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, molecular biology, or metabolic engineering with extensive computational research and lab experience. Certifications/Licenses Required Knowledge, Skills, and Abilities Preferred Qualifications A background in
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Minimum Education and Experience A PhD degree in a relevant area of sciences, such as Nutritional Sciences, Biochemistry, Cell and Molecular Biology/Physiology, Biochemical Nutrition, is required
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Pension Eligibility ABP Qualifications Minimum Education and Experience PhD or equivalent degree in neuroscience, neurobiology, molecular biology, biochemistry, psychology, genetics, pharmacology, or a
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Internal Number: 273086 Minimum Education and Experience: This position requires a PhD or equivalent and experience with the C. elegans model system. City: Piscataway State: NJ Location: Rutgers University
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one programing language (e.g., R, STATA). · Excellent quantitative analytical skills, particularly in longitudinal modeling, administrative data analyses, and causal inference methods. Understanding