Job Description
The 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.
Key Responsibilities:
1. 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.
2. 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.
3. 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.
4. Develop Machine Learning Models: Contribute to the development and implementation of machine learning models for data analysis and target identification.
5. Communicate Findings: Support the team in interpreting results and presenting scientific data to both internal and external stakeholders.
6. Collaborate with Teams: Work with cross-functional teams to leverage computational methods in therapeutic development.
Basic Qualifications:
1. Bachelor’s or Master’s degree in bioinformatics, computer science, computational biology, or a related field.
2. Some experience in a relevant academic or industry setting.
3. Proficiency in programming, particularly Python, with a solid understanding of data analysis and visualization techniques.
4. Familiarity with omics data types (e.g., RNA-seq) and basic machine learning concepts.
5. Strong problem-solving skills and a desire to learn.
Qualifications:
1. Exposure to immunology or experience with biological data analysis.
2. Familiarity with cloud computing and data management environments.
3. Collaborative work style and effective communication skills.
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