Proteomics Specialist

Guidehouse•Rockville, MD

8d•$98,000 - $163,000•Hybrid

About The Position

We are seeking a Computational Biologist with strong extensive proteomics experience to join our Bioinformatics team at the NIH. The computational biologist will independently support –omics projects, specifically, proteomics projects as well as others as needed, initiated by researchers and clinicians at the National Institute of Allergy and Infectious Diseases (NIAID) in the National Institutes of Health (NIH). This opportunity is a full-time position with Guidehouse and can be remote or on-site at NIH in Rockville, MD. The candidate will operate in a multi-disciplinary group of scientists who provide support, training, and consultation services to the research community in the areas of bioinformatics and computational biosciences. The successful candidate for this position will be well-versed in proteomic methodologies, including but not limited to traditional to high-throughput technologies, self-directed professional who takes ownership of projects and acts autonomously to set priorities and drive results, highly collaborative, and will provide mentorship and leadership as a proteomics expert. Experience with designing proteomic projects and conducting data analysis using relevant scientific computing software and tools, open-source libraries, data-intensive workloads, and distributed high-performance computing systems is highly desirable. The successful candidate must have excellent written and verbal communication skills to interact with the research community and find the right solution for their diverse scientific analysis and computing needs.

Requirements

FOUR (4) years hands on experience with either Computational Biology or Bioinformatics
Ph.D. (or other graduate degree with equivalent experience) in computational biology, bioinformatics, proteomics or related life, physical, or computational sciences with at least two[P[1] [GR2] publications in high-impact journals demonstrating the use or development of proteomics methods
Good understanding of high-throughput proteomic technologies, protein-biology, molecular biology, and proteomics software (e.g., MaxQuant, Proteome Discoverer, Skyline, Spectronaut, FragPipe, Scaffold Quant, etc.)
Demonstrated proficiency in the analysis of large-scale proteomics data ( LC-MS/MS, label-free and labeled-based quantitative proteomics, TMT, iTRAQ, post-translational modification, Olink, Somascan, etc.), proteomics file types (mzML, MGF, pepXML, IDML, etc.) and experienced with a broad spectrum of relevant open-source software or pipelines (Pyteomics, AlphaPeptStats, MSstats, proteoDA, MS-DAP, etc.).
Experience working with relevant proteomics databases and browsers and their annotations (UniProt, PDB, STRING, PRIDE, Human Protein Atlas, and neXtProt)
Proficiency in the use of UNIX/Linux and its command-line environment, including scripting (Python, R, shell, Perl, etc.) as well as experience with code and documentation repositories such as GitHub.
Proficiency in pathway analysis translating protein lists into biological insights using enrichment tools (GO, KEGG, IPA) and protein-protein interaction network analysis
Experience with a high-performance parallel computing environment (e.g., SLURM, PBS, SGE)
Familiarity with common methods of statistical analysis (linear mixed models, Bayesian approaches) to identify differentially expressed proteins and biomarkers
Strong interpersonal, presentation, written, and oral communication skills to convey computational biology principles and concepts to non-specialists in a clear and precise manner and advise on relevant software and tools with a dedication to customer satisfaction
Ability to work independently or as part of a multi-disciplinary team
Excellent troubleshooting and problem-solving skills, including the ability to learn new software quickly
Ability to concurrently work on multiple complex projects with effective time management skills, a high level of personal and professional drive and initiative, and attention to detail
Proficiency with the use of open-source bioinformatics applications employing ontologies, pathways, and/or networks, at both the individual protein and proteomic scales
Familiarity with problems and bottlenecks associated with storage and management of proteomics-scale data
Must be able to obtain and maintain a Federal or DoD "public trust"; candidates must obtain approved adjudication of their public trust prior to onboarding with Guidehouse. Candidates with an active public trust or suitability are preferred

Nice To Haves

Experience with one or more other omics analysis pipelines (QC, normalization, visualization, results reporting) and technologies listed below
Cytometry (traditional, spectral, mass/CyTOF cytometry, flowJo, OMIQ, Cytobank; relevant R and python libraries such as flowCore, CATALYST, diffcyt, cytofkit, FlowSOM, FlowIO, FlowUtils, etc.)
Single-cell and spatial omics analysis using platforms such as 10x Genomics (GEX, Multiome, Visium, Xenium), Parse Biosciences, MERFISH, CITE-seq, with demonstrated experience in R/Python-based analysis frameworks (Seurat, Scanpy, etc.)
Metabolomics/lipidomics (LC-MS, GC-MS, CE-MS, NMR for targeted or untargeted analysis; relevant R and Python libraries such as xcms, SpectriPy, MetaboAnalystR, pyOpenMS, Asari, pcpfm, TidyMS, lipidr, LipidMS, mixOmics, Lipydomics, LipidFinder, etc.)
Proficiency in the analysis and integration of multi-omics datasets involving proteomics (e.g. integration with other omics data such as cytometric, transcriptomics, genomics, metabolomics, etc.)
Experience constructing pipelines in open architecture platforms (e.g. Snakemake, nextflow, or R targets), including end-to-end tasks for proteomics analysis tools
Strong background in molecular/cellular biology, immunology, and/or infectious disease research, including “bench” experience.

Responsibilities

Implement, design, develop, and innovate current and emerging computational biology and bioinformatics algorithms to analyze, manage, interpret, visualize, and illustrate original scientific data
Enter into scientific collaborations with physicians and scientists that include the potential for authorships and acknowledgements in publications
Gather detailed requirements from stakeholders and identify existing tools to perform the novel analyses or develop algorithms/tools to perform the analysis
Document and manage collaborative and consultant assistance and training provided to researchers
Provide on-demand support and troubleshooting to researchers in the use of computational biology software
Research, design, and deliver training materials to effectively communicate, promote, and advance computational biology techniques and software usage by NIH researchers
Remain abreast on current and emerging computational biology literature, technologies, and tools
Partner with software developers to integrate proteomics software solutions within enterprise platforms

Benefits

Medical, Rx, Dental & Vision Insurance
Personal and Family Sick Time & Company Paid Holidays
Parental Leave
401(k) Retirement Plan
Group Term Life and Travel Assistance
Voluntary Life and AD&D Insurance
Health Savings Account, Health Care & Dependent Care Flexible Spending Accounts
Transit and Parking Commuter Benefits
Short-Term & Long-Term Disability
Tuition Reimbursement, Personal Development, Certifications & Learning Opportunities
Employee Referral Program
Corporate Sponsored Events & Community Outreach
Care.com annual membership
Employee Assistance Program
Supplemental Benefits via Corestream (Critical Care, Hospital Indemnity, Accident Insurance, Legal Assistance and ID theft protection, etc.)