Biomedical Information Analyst- II
Immediate opportunity for a Biomedical Informaiton Analyst II. Assist lab members in performing bioinformatics data analysis, interpretation, integration, communication and reporting Apply computation, mathematical and statistical methods to extract small molecule metabolite spectra from high resolution LC/MS data. Familiarity with metabolomics data is a plus. Curate and manage internal metabolite databases and MS/MS spectral libraries. Perform information analysis and annotation. Apply R scripts for univariate and multivariate statistics and exploratory analysis and visualization of high dimensional data statistical and machine learning algorithms to efficiently access and analyze textual information. Experience with batch queries and analytics platforms for semantic and text analysis. What will you do? Provide bioinformatics support and manage data analysis, documentation, and deliverable preparation for the various scientific research projects consisting of metabolomics applications Analyze large scale targeted and untargeted metabolomics data sets Work with team on data analysis and data management on various large datasets. In silico annotation and identification of features identified by LC-MS experiments Generate, analyze, and interpret univariate and multivariate data sets. Communicate approaches and interpretation of findings to other stakeholders Implement and extend software for the analysis of untargeted metabolomics data Organize and analyze results, and communicate and present findings in team meetings Analyze and interpret LC/MS data and translate findings into cell culture media and process advances Identify and utilize appropriate feature selection and dimensionality reduction techniques to support data analysis Statistical Design of Experiment (DOE) experience is a plus
Minimum B.S in a science related field: Bioinformatics, Life Sciences, Molecular Biology, Computer Science or related field. Masters or PhD degree is preferred. Experience with high resolution, accurate mass LC/MS data files, data/file transfer, data mining and visualization; familiarity with MS and MS/MS database curation. Prior experience in the analysis of metabolomic data sets is highly desired but not required. Proficiency with one or more programming languages such as R, Python, C++, or Java. Knowledge of MATLAB is a plus. Basic understanding of database querying languages such as SQL. TOP 3 Skillsets-Experience Analyzing with life science data. R programming skills required (Other programming nice to have). Biostatistics (statistical analysis) Experience querying and extracting information from public and proprietary databases is a plus Ability to manage large bioinformatics datasets and assist in the development of automated workflows is a plus Ability to multi-task across projects; Excellent time management and completing tasks on time Management of metabolomics data sets including integration with data available from public sources
For immediate consideration please email resume to Neha Potdar at firstname.lastname@example.org.
Job Type: Contract
Location: Cambridge, MA
Job ID: 20-01106
Date Updated: February 18, 2020