SCIENTIST, COMPUTATIONAL BIOLOGY

My name is Bhawna and I'm a Technical Recruiter with ACS Group, a leading information technology services and workforce solutions company.

We currently have an opportunity for a "Computation Biologist" with one of our clients in the "Cambridge MA" area.

Job Title: Computation Biologist/Scientist

Job Location: Cambridge MA

Duration: 12+ Months W2 Contracts

Summary

We are seeking a highly motivated Proteomics Bioinformatician to augment our computational capacity in analyzing large-scale proteomics datasets. You will work within a matrix of proteomics scientists, computational biologists and data engineers to design and improve proteomic) data processing pipelines, perform data quality control and carry out quantitative analyses on proteomics datasets generated from various acquisition routes. You will also collaborate with internal and external collaborators to guide experimental design, derive analytical plans and generate reports and visualizations.

Responsibilities

• Maintain and improve proteomics data processing pipelines
• Preform the quality-control (normalization/imputation/filtering) and analysis of proteomics data (secondary and tertiary analyses)
• Document workflows and ensure data injection, versioning control and curation using in-house built data warehouse
• Present results and conclusions to internal and external stakeholders

Qualifications

• M.Sc or Ph.D. in Bioinformatics, Computer Science, Molecular Cell Biology, Biochemistry, Analytical Chemistry or related fields. Minimum 1-3 years research experience (academics/industry)
• Experience in processing proteomics data and understanding of the complexity of proteomics data structure is a must.
• Strong experience in multivariate, pathway and network-based analyses.
• Fluency in R, Bioconductor and data visualization tools (ggplots, plotly)
• Familiarity with proteomics data pipelines for data-dependent and independent acquisitions and data types from MaxQuant, Fragger, DIA_NN, Spectranaut, Peaks workflow.
• Experience in developing methods and new approaches for analyzing large-scale proteomics datasets is desirable
• Familiarity with other programming languages (Python, Java, C++), relational or graph database and data manipulation tools (dplyr, numpy, pandas) is highly desirable
• Familiarity with shell scripting and cloud computing infrastructure (AWS batch, lambda, Athena, Redshift, Google Cloud BigQuery) is desirable
• Familiarity with web app development R shiny/Flask/Django will be a plus.

Bhawna Panwar