Associate Scientist – Bioanalytical

Posted on January 19, 2017

Overview

Job Title

Associate Scientist – Bioanalytical

Description

We are seeking an entry level scientist to join the Bioanalytical Sciences group and contribute to our metabolomics and mechanism of action efforts. The preferred candidate will possess a deep understanding of bioanalytical method development, sample processing/purification, and various LC-MS or GC-MS techniques. This scientist will be adept at handling large ‘omics datasets to elucidate the discovery and validation of clinical biomarkers. The candidate is expected to be able to contribute across multiple inter-disciplinary projects in an innovative and fast-paced Silicon Valley team environment.

Responsibilities
  • Establish bioanalytical assays for the quantification of small molecules and low molecular weight biomarkers in numerous matrices via rigorous method development
  • Hands-on processing of Clinical and ADME samples (e.g. blood, urine, CSF, etc.) using multiple enrichment and purification techniques
  • Collaborate with discovery scientists to selectively enrich and quantitate new targets in mechanism of action studies
  • Use robotic liquid handlers to increase throughput for standard bioanalytical processing
  • Liaise with CompSci to streamline data processing, statistical analysis, and dissemination
  • Operate, maintain, and troubleshoot Shimadzu LC systems and Sciex MS systems

Qualifications

Essential Experience
  • Ph.D. in chemistry, biochemistry, or related field with 1 – 3 years of experience
  • In-depth knowledge of multiple LC-MS or GC-MS techniques is a must
  • Proficient with multiple analyte enrichment methods from tissue, biofluids, or cellular systems
  • Prior experience in energy metabolism, inflammation, or neurological programs is preferred
  • Expertise in metabolomics, lipidomics, glycan or flux analysis is desired
  • Proven track record for high level of inter-disciplinary problem-solving and innovation
  • Ability to adapt to rapidly changing priorities and deadlines
  • Efficient at identifying and troubleshooting critical components in complex systems
  • Excellent time management, communication, and team skills

Personal

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