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Associate Scientist - Biology II

Employer
US Tech Solutions
Location
Santa Monica, California, US
Salary
Competitive
Closing date
Jun 28, 2022

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Sector
Academic / Research
Field
Conservation science
Discipline
Biology
Salary Type
Salary
Employment Type
Full time
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Job Description

We are seeking an individual with a background in immunology and strong interest in investigating novel approaches to achieve drug-free remission or cure of HIV infection.

Primary responsibilities
  • Designing, validating and performing novel cell-based immunology and virology assays
  • Evaluating new targets and therapeutic approaches for curing HIV
  • Supporting in vivo proof-of-concept studies in models of chronic HIV infection
  • Understanding properties of the latent HIV reservoir in experimental models and clinical settings
  • Interpreting results, proactively troubleshooting technical challenges and recommending potential solutions based on personal observations and/or literature searches.
  • Plans and executes experiments that support research activities and project goals.
  • With general guidance and direction selects appropriate methods and techniques in performing experiments.
  • Recommends creative solutions to problems, researches new methods and techniques and may proactively seek out senior personnel to discuss potential solutions to problems.
  • Clearly presents results of work, interprets data, and draws conclusions regarding presented material and nature of work.


Skills / Qualification Required
  • Typically requires a BS/BA degree in Immunology, Microbiology, Molecular and Cell Biology or other related life science discipline and minimum 9+ years of relevant experience.


The ideal candidate will have hands-on experience in one or more of the following techniques:
  • Immune cell functional assays, multi-color FACS, primary cell isolation and culture, ELISA/Luminex, molecular biology techniques such as RNA/DNA isolation, qPCR, cloning and virus production.
  • The candidate must be able to process data and evaluate data quality, including recognizing anomalous and inconsistent results.
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