Collabera
Bioinformatics Analyst IIIII Hybrid
Collabera, Cambridge, Massachusetts, us, 02140
Job DescriptionImmunology 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.
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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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.
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.
#J-18808-Ljbffr