Intern – Translational Biology (AI/ML)

Cytokinetics • South San Francisco, CA

6d • $35 - $40 • Onsite

About The Position

Cytokinetics is a specialty cardiovascular biopharmaceutical company, building on its over 25 years of pioneering scientific innovations in muscle biology, and advancing a pipeline of potential new medicines for patients suffering from diseases of cardiac muscle dysfunction. At Cytokinetics, each team member plays an integral part in advancing our mission to improve the lives of patients. We are seeking tenacious, compassionate, and collaborative individuals who are driven to make a positive impact. This is a paid internship at our South San Francisco headquarters. The program is for approximately 12 weeks beginning in late May/early June. Under the mentorship of the Translational Biology (TB) team, the intern will work closely with cross-functional teams in preclinical and clinical research to contribute to translational biomarker discovery efforts using large-scale population biobank datasets. The TB team analyzes biological and clinical data to support target prioritization and advance clinical development programs. The TB intern will develop and validate AI/ML-enabled statistical methods and/or computational workflows to analyze genetic, clinical, and imaging data, and identify predictive and prognostic biomarkers. The TB intern will have the opportunity to make meaningful contributions to high-impact research projects, and may have the opportunity to publish their work.

Requirements

• Currently enrolled in university, pursuing a Master’s Degree or PhD (PhD preferred) in Human Genetics, Bioinformatics, Computational Biology, Biomedical Informatics, Computer Science, or a related field
• Experience in applying AI/ML to biological or clinical problems
• Experience in working with genetic and/or imaging datasets
• Solid understanding of statistical modeling and analytical methods used in machine learning and data science
• Excellent communication and interpersonal skills

Nice To Haves

• Strong plus: evidence of strong computational and statistical analysis skills (e.g., publications, conference presentations, and/or a GitHub portfolio)

Responsibilities

• Curate, harmonize and analyze multi-modal biobank datasets (genetic data, phenotypes/EHR-derived traits, imaging, proteomics/transcriptomics where available) relevant to cardiovascular and neuromuscular disorders
• Develop and implement statistical genetics methods and/or AI/ML workflows for translational biomarker discovery, risk prediction and novel target prioritization (including model development, evaluation and interpretation)
• Evaluate the utility of protein language models for variant interpretation and improving statistical power for rare variant association tests
• Apply causal inference approaches where appropriate (e.g., Mendelian randomization, colocalization, fine-mapping) to strengthen biological plausibility and therapeutic hypotheses
• Build end-to-end, reproducible analysis pipeline following best practices for cloud computing (AWS/GCP) and data science
• Communicate findings through clear documentation, presentations and written summaries for both computational and experimental audiences

What This Job Offers

• Career Level: Intern
• Number of Employees: 251-500 employees