Life Sciences Research Specialist, Python

This is a fully remote position, open to applicants in United States, +4 more countries.

📋 Description

• Formulate and address technically challenging scientific issues within your area of expertise.

• Create reproducible analyses, models, simulations, and data-processing workflows utilizing Python.

• Examine and interpret biological or biomedical datasets using suitable computational techniques.

• Assess scientific solutions and Python scripts for precision, clarity, thoroughness, and reproducibility.

• Detect inaccuracies in scientific reasoning, computational approaches, assumptions, and code execution.

• Implement relevant statistical and computational methods to confirm research outcomes.

• Record methodologies, assumptions, and solutions in a clear and organized fashion.

• Participate in initiatives aimed at assessing and enhancing advanced AI systems.

• Merge scientific research knowledge with practical software capabilities across biology and related fields.

⛳️ Requirements

• Master’s or PhD in a pertinent life sciences field, such as Biology, Biomedical Sciences, Bioinformatics, Neuroscience, Genetics, Computational Biology, or a similar discipline.

• Significant research experience evidenced by publications, thesis work, computational endeavors, industry research, or comparable achievements.

• Proficient Python programming skills, especially for scientific computing, data analysis, modeling, or simulation.

• Capability to independently write, comprehend, debug, and validate Python scripts.

• Experience with scientific or biological datasets and interpreting computational findings.

• Strong analytical skills and the capacity to assess scientific methods and technical conclusions.

• Exceptional written English skills with the ability to convey complex scientific ideas clearly.

• Native English speaker.

• Availability for around 15 hours per week.

• Flexibility to work varied hours and days, including weekends if desired.

🏝️ Benefits

• Flexible schedule—select your working hours and days, including weekends if you prefer.

• Approximately 15 hours per week.

• Output-based remuneration with payment per task that aligns with project requirements.