Bioinformatics Analyst in Cambridge, MA

Hybrid role (3 days onsite and 2 days remote)

• Utilize publicly available single-cell datasets to build comprehensive single-cell atlases
• ScRNASeq data
• Please do not submit manager level candidates need someone who has done hands on work
• Python Packages exp needed (panda analytical data, scan Pi, Machine learning)
• Bioinformatics exposure
• Strong background in python programming
• SCRNA Seq and Elisa
• ML models
• Building Atlas using ScRNAseq data
• biological data
• Master’s or PhD degree will work
• Computational Analytical roles and no wet lab exp is needed
• Heavy on Python
• Machine learning exp

Top skills

• Python Packages
• SCRNA Seq data analysis

Position Overview:

• Systems Immunology and Immune Profiling center (SI/IPC) team in Cambridge, Massachusetts is seeking a highly skilled contractor with expertise in bioinformatics and computational biology, with a strong emphasis on proteomics analysis, including Cytometry by Time Of Flight (CyTOF), Imaging Mass Cytometry (IMC) and Mass Spectrometry (MS).
• The successful candidate will play a critical role in analyzing internal datasets and advancing our mission to identify novel therapeutic targets for autoimmune and chronic inflammatory diseases.

Key Responsibilities:

• Perform advanced analysis of high-dimensional proteomics data, including CyTOF, Flow Cytometry, and MS, to generate actionable insights into disease mechanisms.
• Help develop and optimize computational workflows and pipelines for processing, analyzing, and interpreting proteomics datasets.
• Perform image-based quantification of proteins using IMC, focusing on spatial distribution and co-localization of immune cells and other tissue components in situ.
• Collaborate with multidisciplinary teams, including immunologists, data scientists, and biologists, to interpret proteomics data and translate findings into preclinical and clinical research applications.
• Present complex analytical approaches and results to both technical and non-technical stakeholders, effectively communicating the scientific rationale and implications.

Skills and Qualifications:

Education:

• M.S. in bioinformatics, computational biology, proteomics, biochemistry, or a related field.

Technical Expertise: 

• Proficiency in programming languages such as R and Python, and experience working in Unix/Linux environments.
• Knowledge of statistical methods and machine learning techniques applicable to the analysis of large-scale proteomics datasets.

Preferred Skills: 

• Experience with computational methods for protein quantification, identification of post-translational modifications, and protein-protein interaction network analysis.
• Familiarity with CyTOF, spatial CyTOF (IMC), and Flow Cytometry data analysis techniques is desirable.
• Expertise in proteomics data analysis, including Mass Spectrometry (MS)-based proteomics, and familiarity with related software tools or other proteomics data analysis platforms.
• Strong communication skills with the ability to present complex data to both scientific and non-scientific audiences.
• A proactive and collaborative approach to problem-solving in a dynamic, fast-paced research environment.
• Ability to manage multiple projects simultaneously and adapt to changing priorities.
• Contribute to the preparation of scientific publications, presentations for conferences, and regulatory submissions (if any).

Key Competencies:

• Demonstrated ability to work independently while contributing effectively to multidisciplinary teams.
• Organizational skills with the capacity to manage competing priorities and deliver high-quality work within deadlines.
• Commitment to continuous learning, innovation, and staying current with the latest developments in proteomics and computational biology.

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