Bioinformatics Analyst in Cambridge, MA

Bioinformatics Analyst II

Hybrid- 2 days onsite 3 days remote

Python models: Being experienced with pandas, numpy, scanpy, anndata, scikit-learn.

Bein familiar with: pytorch or keras, scvi-tools or scarches

Open to candidates who are ready to relocate at their own expense

• Experience will be given first preference
• PhD will also work with relevant expertise
• Master’s degree needed
• Flow CYTOF methods exp needed
• Exp in proteomics and
• Expertise with R and Python exp
• Flow Cytometry Data
• Exp in CYTOF and flow techniques
• Bachelor’s degree with exp will also work
• Computational Analytical roles and no wet lab exp is needed

Must have Top Skills

• Python (Must have)
• Proteomics data (Must have)
• CYTOF Data (Must have)
• R programming (Must have)

What are the top 3-5 skills, experience or education required for this position?

• Ideally Masters degree holders
• 3 years experience for Bioinformatics II
• 5+ could be considered for Bioinformatics III

Duties:

• Immunology team is expanding its early discovery team, focusing on identifying new targets for autoimmune and chronic inflammatory diseases.
• We are looking for a motivated and talented individual to join us as a Computational Scientist.
• In this role, you will contribute to computational analyses that predict drug responses using high-throughput molecular profiling data and support the discovery of new therapeutic targets using high-throughput molecular profiling data.

Key Responsibilities:

• Build a Single-Cell Atlas: Utilize publicly available single-cell datasets to build comprehensive single-cell atlases, enhancing our understanding of cellular heterogeneity in immune system and disease contexts.
• Analyze Single-Cell Data: Assist in the analysis of single-cell RNA-seq, TCR-seq, and BCR-seq data to identify disease-associated regulatory networks and biomarkers.
• Support Multi-Omics Integration: Help integrate various omics data (e.g., gene expression, proteomics) to gain insights into disease mechanisms and identify potential drug targets.
• Develop Machine Learning Models: Contribute to the development and implementation of machine learning models for data analysis and target identification.
• Communicate Findings: Support the team in interpreting results and presenting scientific data to both internal and external stakeholders.
• Collaborate with Teams: Work with cross-functional teams to leverage computational methods in therapeutic development.

Basic Qualifications:

• Bachelor’s or Master’s degree in bioinformatics, computer science, computational biology, or a related field.
• Some experience in a relevant academic or industry setting is preferred.
• Proficiency in programming languages, particularly Python, with a solid understanding of data analysis and visualization techniques.
• Familiarity with omics data types (e.g., RNA-seq) and basic machine learning concepts.
• Strong problem-solving skills and a desire to learn.

Preferred Qualifications:

• Exposure to immunology or experience with biological data analysis.
• Familiarity with cloud computing and data management environments.
• Collaborative work style and effective communication skills.

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