Postdoctoral Research Associate in Bioinformatics

About the role

The Biochemistry and Biotechnology Group (B-TEK) in the Bioscience Division is seeking candidates interested in utilizing and developing proteomics, metabolomics, and/or lipidomics pipelines to deeply characterize a variety of sample types, coupled with bioinformatics utilizing data generated from high resolution platforms. Candidates skilled in handling large scale proteomics, metabolomics or lipidomics data are encouraged to apply. Candidates should be able to process data both quantitatively and qualitatively, and ideally have experience developing targeted, quantitative workflows.

Responsibilities

• Process and analyze large-scale proteomic, metabolomic, or lipidomic data
• Develop targeted methods for monitoring select biomarker panels including proteins and small molecules
• Characterize the in vitro, molecular response following exposure to toxicants of concern
• Support multiple projects with a National Security application
• Work independently to support multiple projects all of which have a National Security application
• Develop sample preparation workflows for biofluids including saliva, urine, and/or blood
• Implement quality control standards for metabolomics, including the use of reference, quantitative, process control, and system performance standards
• Build in-house metabolite libraries and utilize publicly available resources for metabolite identification
• Apply machine learning and statistics to develop robust biomarker panels
• Harmonize different -omics data sets for pathway analysis and correlative studies
• Operate, maintain, and troubleshoot various mass spectrometers, including Thermo Fisher Orbitrap platforms
• Use software packages such as Proteome Discoverer, Compound Discoverer, or Tracefinder
• Develop and apply computational workflows
• Conduct network analysis (e.g., relational or graph-based data)
• Translate analytical findings into actionable insights
• Proficient in at least one programming language (e.g., Python or R), and knowledge of mass spectrometry data

Requirements

• Well-established record of publications in peer-reviewed journals
• Communication skills evidenced by reports, publications, and oral presentations at conferences
• Demonstrated experience using bioinformatics tools and developing computational workflows
• Experience working with high-dimensional and complex datasets
• Fundamental understanding of mass spectrometry with a focus on -omics and their pipelines
• Hands-on experience in regards to sample preparation, data acquisition, and data analysis
• Ability to obtain a Q clearance, which requires US Citizenship

Qualifications

• A Ph.D. in a STEM field completed within the last five years or to be completed by commencement of appointment
• Experience handling/processing a wide range of proteomic/metabolomic data such as DDA, DIA, de-novo, top-down, etc., including data from large scale studies
• Experience developing quantitative methods for small molecule and protein analysis
• Ability to implement elements of quality control to account for background, extraction efficiency, quantitative precision, reproducible liquid chromatography separations, and standards/sample pools for feature identification
• Ability to build in-house metabolite libraries and utilize publicly available resources is preferred (e.g., NIST and/or MzCloud)
• Familiarity applying machine learning and statistics to develop robust biomarker panels
• Familiarity with harmonizing different -omics data sets for pathway analysis and correlative studies
• Knowledge of mass spectrometry -omics for biomarker discovery using proteomics, metabolomics, and/or lipidomics
• Experience with the operation, maintenance, and troubleshooting of various mass spectrometers, including Thermo Fisher Orbitrap platforms
• Familiarity using software packages such as Proteome Discoverer, Compound Discoverer, or Tracefinder
• Strong background in multivariate statistical analysis and predictive modeling
• Proficiency in data visualization and communicating analytical results
• Experience conducting network analysis (e.g., relational or graph-based data)
• Expertise in machine learning and software development
• Demonstrated ability to translate analytical findings into actionable insights
• Proficient in at least one programming language (e.g., Python or R), and knowledge of mass spectrometry data

Skills

• Strong background in multivariate statistical analysis and predictive modeling
• Proficiency in data visualization and communicating analytical results
• Experience conducting network analysis (e.g., relational or graph-based data)
• Expertise in machine learning and software development
• Demonstrated ability to translate analytical findings into actionable insights
• Proficient in at least one programming language (e.g., Python or R), and knowledge of mass spectrometry data

Benefits

Los Alamos National Laboratory offers a comprehensive benefits package including:

• PPO or High Deductible medical insurance with the same large nationwide network
• Dental and vision insurance
• Free basic life and disability insurance
• Paid childbirth and parental leave
• Award-winning 401(k) (6% matching plus 3.5% annually)
• Learning opportunities and tuition assistance
• Flexible schedules and time off (PTO and holidays)
• Onsite gyms and wellness programs
• Extensive relocation packages (outside a 50 mile radius)

Pay

Details about pay will be provided during the interview process.

Schedule

Details about the schedule will be provided during the interview process.