Entry-Level Computational Biologist: Data & Analysis

Stanford Reglab; United States; On-site; USD 55,000 - 85,000; Full time

Job summary

The Beckman Center for Molecular and Genetic Medicine at Stanford University is seeking an entry-level Computational Specialist to support data analysis and data management across three shared research facilities: CSIF, PAN, and the FACS Facility. This role provides an opportunity to apply computational skills to diverse biological data in a collaborative environment.

Ideal for recent graduates with programming experience who want hands-on involvement in research projects, experimental design,

Qualifications

• Bachelor's degree or higher in a life science or related field.
• Experience applying computational skills to biological data.
• Ability to learn and use computer programs, databases and scientific applications.
• Strong record-keeping and organizational skills.

Responsibilities

• Plan approach to experiments in support of research projects.
• Independently conduct experiments; maintain detailed records of experiments and outcomes.
• Apply theories and methods of life sciences to interpret analyses and suggest procedural modifications.
• Review literature to stay current with new procedures and apply learnings.
• Contribute to publication of findings and prepare procedures, presentations, and proposals.
• Maintain lab stock, inventory and safety records; provide general lab support.
• Assist with orientation and training of new staff or students on lab procedures.

Skills

Data analysis

Computational thinking

Programming experience

Record keeping

Laboratory data management

Quick learner

Education

Bachelor's degree in related scientific field

Job description

The Beckman Center for Molecular and Genetic Medicine at Stanford University is seeking an entry-level Computational Specialist to support data analysis and data management across three shared research facilities: CSIF, PAN, and the FACS Facility. This role provides an opportunity to apply computational skills to diverse biological data in a collaborative environment.

Ideal for recent graduates with programming experience who want hands-on involvement in research projects, experimental design,