JOB DESCRIPTION
The Discovery Proteomics group at our South San Francisco campus is tasked with developing and
implementing proteomic characterization technologies in support of Amgen’s early discovery pipeline
In this vital role you will you will conduct statistical analysis, data ingestion, and computational pipeline development for internal and external mass spectrometry-based and other type of proteomics data to support biomarker discovery, target validation, experimental design, and mechanism‐of‐action studies. You will work closely with other lab-based scientists in the Discovery Proteomics group, genomics, and software engineers in the Research Informatics team to support multi-omics
data integration.

ROLE RESPONSIBILITIES
Enable Amgen’s preclinical pipeline through delivery of innovative technologies and technical expertise.
Implementation of data analysis, management, and visualization strategies for the complex proteomics and posttranslational data generated by mass spectrometry and other technologies.
Develop and establish computational solutions for differential protein expression analysis, protein turnover rate estimation, and protein-protein interaction identification.
Work across genomic and proteomic platforms, and potentially other ‘omic’ platforms, for data integration and mining, applying available external resources where appropriate.

PREFERRED QUALIFICATIONS:
Doctorate degree, Master’s degree plus 4 years of relevant experience, Bachelor’s degree plus 6 years of relevant experience.
Proficiency in Python/R/SQL/Java and familiarity with analytic techniques/packages necessary for statistical analysis, data processing, data visualization, and machining learning
Good practice in coding project management and reproducible data analysis.
Solid understanding in the Unix/Linux and cloud computing (AWS) environment.
Experiences in analyzing large scale protein interactions, protein turnover, and/or posttranslational modification studies.
Knowledge of proteomics data processing pipeline such as Proteome Discoverer, Spectronaunt, Skyline, MaxQuant, DIANN, MSstats, or OpenMS.
Strong background in biology or chemistry, especially as it pertains to human disease in the fields of Immunology, Oncology, Inflammation, and Cardiometabolic Disease.
Basic understanding in genomics and transcriptomics technologies and data properties.

FOR MORE DETAILS AND APPLY THE POSITON:
http://adtrk.tw/tp/rj6-vaM5-y-K