Life Sciences Research Expert (Python)

About the Role

Pay: $60–$120/hour Schedule: Flexible—you choose the hours and days you work, including weekends if desired micro1 is seeking experienced life sciences researchers with strong, hands-on Python skills to contribute to projects focused on evaluating and improving advanced AI systems. In this role, you will apply your scientific expertise to create, solve, and review challenging research problems within biology and related fields. You will use Python to analyze scientific data, develop reproducible solutions, validate computational results, and identify errors in technical reasoning or code. Areas of Expertise We are particularly interested in candidates with expertise in one or more of the following: • Medicine and biomedical science • Computational biology • Neuroscience • Molecular and cellular biology • Biotechnology and bioinformatics • Genetics and genomics • Ecology and evolutionary biology • Biostatistics or biological data science • Etc. Process • Apply to the role and complete the screening questions. • Complete an AI interview of approximately 30 minutes. • Complete the hiring manager review. Compensation Structure Compensation is output-based. Experts are paid per task that meets the project specifications. The time required to complete each task may vary depending on the expert’s experience and workflow. Minimum submission requirements apply.. Start Timeline & Availability We typically fill roles within 48 hours and are looking for experts who are ready to begin immediately. If selected, you will be expected to start your first task within 24–48 hours of completing onboarding.

Responsibilities & Tasks

• Create and solve technically rigorous scientific problems within your area of expertise.
• Develop reproducible Python-based analyses, models, simulations, or data-processing workflows.
• Review scientific solutions and code for correctness, clarity, and completeness.

Qualifications & Requirements

• PhD, MD, or master’s degree with substantial research experience in a relevant life sciences discipline.
• Strong scientific or applied research background demonstrated through publications, thesis work, computational projects, industry research, or equivalent accomplishments.
• Practical Python experience for scientific computing, data analysis, modeling, or simulation.
• Familiarity with tools such as NumPy, pandas, SciPy, Matplotlib, scikit-learn, Jupyter, or relevant domain-specific libraries.