Postdoctoral Fellow

Role Summary

Postdoctoral Fellow at Cytokinetics in South San Francisco focused on muscle biology and drug discovery processes. Works with a mentor to develop an independent research project while gaining foundational knowledge in target discovery, technology or model development, and mechanism of action of therapeutics. The program aims to train scientists for biotech or academic careers dedicated to muscle-related human diseases.

Responsibilities

• The fellow will spearhead a computational biology project to harmonize multi-modal clinical and imaging data across population biobanks related to human skeletal muscle function, using machine learning and deep learning to categorize phenotypes and correlate them with genetic variation and clinical severity scores, with aim of a high-impact publication.
• Play an integral role in championing new bioinformatic tools and workflows to enable discovery of novel therapeutic targets, conducting research independently and in a team-based setting.
• Provide regular project updates and progress in small and large group settings, offering scientific and technical expertise to advance discovery programs.

Qualifications

• PhD in computational biology, computer science, bioinformatics, human genetics, or related field
• Demonstrated expertise in multidimensional data analysis
• Experience analyzing multimodal data from population biobanks such as UK Biobank, All of Us, FinnGen or Genomics England is highly desirable
• Proven experience applying AI/ML techniques to biological problems
• Articulated career goals in research (biotech or academia)
• Track record of research excellence, independent critical thinking, and ability to design, execute, and interpret experiments as demonstrated by publications, presentations, fellowships, and grants
• Enthusiasm for team-based, multi-disciplinary work with strong verbal and written communication skills
• Commitment to a 1-2 year research and enrichment program including travel stipends and external training/coursework beyond mentor training

Skills

• Data analysis and interpretation of complex, multimodal datasets
• Machine learning and AI techniques applied to biomedical problems
• Collaborative research and effective scientific communication