Life Science Research Specialist (Remote | $60–$120/hr)

Synthires; California; Remote; USD 83,000 - 165,000; Full time

Benefits offered by this job

Fully remote worldwide

Flexible schedule

15 hours per week

Job summary

Synthires is seeking experienced life sciences researchers with strong Python skills to contribute to projects evaluating and improving AI systems. You will apply scientific expertise to biology, medicine, and related life sciences, using Python to analyze data, develop reproducible solutions, and validate results.

You will review scientific solutions and Python code for correctness and clarity, and provide feedback to support the evaluation and improvement of advanced AI systems.

Qualifications

• Strong hands-on Python experience for scientific computing and data analysis.
• Solid research background in life sciences disciplines.
• Expertise in biology, medicine, neuroscience, computational biology, or bioinformatics.

Responsibilities

• Create and solve technically rigorous scientific problems within your area.
• Develop reproducible Python analyses, models, simulations, and data workflows.
• Analyze scientific datasets with appropriate computational methods.
• Review Python code for correctness, clarity, and completeness.
• Validate computational results and identify errors in reasoning or implementation.
• Apply domain knowledge to assess quality and reliability of AI outputs.
• Provide structured feedback to support evaluation of advanced AI systems.

Skills

Python

Scientific computing

Data analysis

Analytical skills

Technical communication

Education

PhD/MD/Master's with research

Tools

NumPy

pandas

SciPy

Matplotlib

scikit-learn

Jupyter

Job description

Compensation: $60–$120 per hour equivalent

Location: Fully Remote (Worldwide)

About the Opportunity

We are 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 across biology, medicine, and related life sciences disciplines. 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 areas:

• Medicine and Biomedical Science
• Computational Biology
• Molecular and Cellular Biology
• Biotechnology and Bioinformatics
• Genetics and Genomics
• Ecology and Evolutionary Biology
• Biostatistics and Biological Data Science

Key Responsibilities

• Create and solve technically rigorous scientific problems within your area of expertise.
• Develop reproducible Python-based analyses, models, simulations, and data-processing workflows.
• Analyze and interpret scientific datasets using appropriate computational methods.
• Review scientific solutions and Python code for correctness, clarity, and completeness.
• Validate computational results and identify errors in scientific reasoning, methodology, or implementation.
• Apply domain knowledge to assess the quality and reliability of AI-generated scientific outputs.
• Provide clear, structured feedback to support the evaluation and improvement of advanced AI systems.

Required Qualifications

• Strong hands-on Python experience for scientific computing, data analysis, modeling, or simulation.
• A solid scientific or applied research background in a relevant life sciences discipline.
• Expertise in at least one relevant area, such as biology, medicine, neuroscience, computational biology, or bioinformatics.
• Ability to analyze scientific problems, validate results, and evaluate technical solutions.
• Strong analytical, problem-solving, and technical communication skills.

Preferred Qualifications

• PhD, MD, or master's degree with substantial research experience in a relevant life sciences discipline.
• Research experience demonstrated through publications, thesis work, computational projects, industry research, or equivalent accomplishments.
• Familiarity with scientific Python tools and libraries, including: NumPy, pandas, SciPy, Matplotlib, scikit-learn, Jupyter
• Experience developing reproducible computational workflows or scientific simulations.

Compensation & Engagement

• Compensation: $60–$120 per hour equivalent, paid per accepted task.
• Work Arrangement: Fully remote, worldwide.
• Time Commitment: Approximately 15 hours per week.
• Schedule: Flexible, with the option to work on weekends.