Job Details

Computational Scientist

Job ID: req1446
Employee Type: exempt full-time
Facility: Frederick: Ft Detrick
Location: PO Box B, Frederick, MD 21702 USA

The Frederick National Laboratory is a Federally Funded Research and Development Center (FFRDC) sponsored by the National Cancer Institute (NCI) and operated by Leidos Biomedical Research, Inc.  The lab addresses some of the most urgent and intractable problems in the biomedical sciences in cancer and AIDS, drug development and first-in-human clinical trials, applications of nanotechnology in medicine, and rapid response to emerging threats of infectious diseases.

Our core values of accountability, compassion, collaboration, dedication, integrity, and versatility serve as a guidepost for how we do our work every day in serving the public’s interest.  

 Position Overview:

PROGRAM DESCRIPTION         

The AIDS and Cancer Virus Program (ACVP) is an integrated, multidisciplinary program that pursues basic and applied studies aimed at improving our understanding of AIDS-associated viruses, including studies intended to facilitate the improved diagnosis, prevention and treatment of HIV infection and AIDS, and AIDS related tumors, particularly those associated with other viruses such as KSHV. The Program consists of five independent but highly interactive research Sections headed by Principal Investigators, whose work spans from fundamental molecular virology through in vitro studies, to in vivo studies in non-human primate (NHP) models, to international viral epidemiology.  The ACVP also has eight Research Support Core Groups (Cores) that provide critical and often unique technical support capabilities to ACVP laboratories and other laboratories within the NCI and NIH, and to extramural investigators.

KEY ROLES/RESPONSIBILITIES

The Computational Scientist will pursue computational research in central areas of research interest at the AIDS and Cancer Virus Program (ACVP). The successful applicant will be responsible for:

• The analysis, interpretation and visualization of complex multi-dimensional biological data sets (including, but not limited to viral sequence data, time series data of plasma virus and biomarker concentrations, flow cytometry data, epidemiological cohort data and microscopy images)
• Work in close collaboration with investigators to develop computational models to generate new hypotheses and glean biological insights from data
• Suggesting and helping to design new experiments
• Synthesizing analysis results into clear presentations for an audience not familiar with computational biology
• Collaborating with investigators on scientific manuscript development, submission, and revision activities with significant co-authorship and first authorship opportunities
• These activities will support a range of research objectives, including the identification of new targets or biomarkers for HIV/SIV viral reservoirs, and better understanding the fundamental aspects of HIV/SIV dynamics, transmission, and virus-host interactions as well as the evolution/immune control of KSHV and other gamma herpesviruses

BASIC QUALIFICATIONS

• Possession of a PhD degree in applied mathematics, biostatistics, computational biology, or related field from an accredited college or university according to the Council for Higher Education Accreditation. (Additional qualifying experience may be substituted for the required education)
• Foreign degrees must be evaluated for U.S. equivalency
• No experience required beyond the PhD degree
• Strong interest in applying computational approaches to investigate biological questions
• Ability to understand and analyze data from complex experimental designs
• Record of scientific achievements including journal publications or poster presentations
• Excellent oral and written communication skills
• Ability to obtain and maintain a security clearance 

PREFERRED QUALIFICATIONS

• Good working knowledge of one or more mathematical or statistical packages (e.g., Mathematica, R)
• Familiarity with differential equations, computer simulations, and statistical inference is desirable
• Capacity to work across a wide range of rapidly changing and divergent research interests

Equal Opportunity Employer (EOE) | Minority/Female/Disabled/Veteran (M/F/D/V) | Drug Free Workplace (DFW)

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