Life Science Research Professional 1 (1 Year Fixed-Term)

About the role

The lab of Dr. Rhiju Das, in the Department of Biochemistry at Stanford University School of Medicine, is seeking a Life Science Research Professional 1 (1 year fixed-term) to support a computational structural biology research project. This position is associated with the Rosetta Commons Research and Mentoring for Postbaccalaureates (RaMP) program, a one-year fellowship in biomolecular structure prediction and design.

Responsibilities

• Plan computational and experimental approaches for RNA structure prediction and AI-based 3D RNA design projects, based on knowledge of RNA biochemistry, structural theory, and machine-learning methods.
• Independently conduct primarily computational work, including developing and running RNA modeling and design pipelines in the Rosetta software environment, applying and fine-tuning AI/deep-learning models, and writing analysis code, along with supporting wet-lab validation; maintain detailed, reproducible records.
• Apply the theories and methods of computational and structural biology to interpret and analyze design and prediction results; compare computational predictions against experimental data and benchmarks, and suggest modifications to models, methods, and protocols in collaboration with senior researchers.
• Review literature on an ongoing basis to remain current with new algorithms, deep-learning methods, and tools in RNA structure prediction and design, and apply learnings to related research.
• Contribute to publication of findings as needed; participate in preparing written documents, code, presentations, and proposals, and present research to internal and Rosetta Commons community audiences.
• Help with general lab and computational resource maintenance as needed, including data and code organization, software environments, and lab stock and safety records.
• Assist with orientation and training of new staff or students on computational tools, lab procedures, and techniques.

Qualifications

• Bachelor's degree in related scientific field.
• Demonstrated performance to use knowledge and skills when needed.
• Demonstrated ability to apply theoretical knowledge of science principals to problem solve work.
• General computer skills and ability to quickly learn and master computer programs, databases, and scientific applications.
• Ability to work under deadlines with general guidance.
• Excellent organizational skills and demonstrated ability to accurately complete detailed work.