Life Sciences Research & Python Specialist (MSc/PhD)
Gramian Consulting Group
·- Location
- India · published · Japan · South Korea · Taiwan · Hong Kong, Hong Kong, Hong Kong · Pakistan
- Type
- Contract
- Department
- Human Resources
- Source
- Workable
Description
About Gramian
Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs.
About the Job
We are looking for Life Sciences Researchers with strong, hands-on Python programming skills to contribute to projects focused on evaluating and improving advanced AI systems.
In this role, you will combine scientific research expertise with practical software skills to create, solve, and review challenging problems across biology and related disciplines. You will develop reproducible Python-based analyses, process scientific datasets, validate computational results, and identify errors in scientific reasoning, methodology, or code.
We particularly welcome Master’s degree holders with strong research and computational experience, as well as PhD holders who have gained practical experience in software engineering, data science, computational research, or other industry data-focused roles. We value candidates who can independently write, understand, debug, and validate code—not simply researchers who have academic knowledge without practical programming ability.
- LOCATION: US, CA, AUS, NZ, UK (native english speakers); South east, APAC
- COMMITMENT: Approximately 15 hours per week
- SCHEDULE: Flexible—you choose your working hours and days, including weekends if preferred.
- COMPENSATION: Output-based, with payment per task that meets project specifications. Minimum submission requirements apply; the time required per task may vary.
Key Responsibilities
Create and solve technically rigorous scientific problems within your area of specialization.
Develop reproducible Python-based analyses, models, simulations, and data-processing workflows.
Analyze and interpret biological or biomedical datasets using appropriate computational methods.
Review scientific solutions and Python code for accuracy, clarity, completeness, and reproducibility.
Identify errors in scientific reasoning, computational methods, assumptions, and code implementation.
Apply relevant statistical and computational techniques to validate research findings.
Document methodologies, assumptions, and solutions in a clear and structured manner.