Life Sciences Researcher (Remote)

Joblet-AI; Índia; Teletrabalho; INR 7 790 000 - 15 581 000; Tempo parcial

Resumo da oferta

Joblet-AI seeks a Life Sciences Research Expert (Python) for a fully remote, international contractor role (~15 hours/week). You will apply Python to analyze biological data, develop reproducible analyses, and review computational results to improve AI systems.

Ideal candidates hold a PhD/MD/Master with substantial research experience, with publications or strong project work in biology or related fields, and proficient use of Python scientific libraries.

Qualificações

• PhD, MD, or master’s with substantial research experience in life sciences.
• Strong scientific background evidenced by publications or projects.
• Hands-on Python experience for scientific computing, data analysis, modeling or simulation.
• Familiar with NumPy, pandas, SciPy, Matplotlib, scikit-learn, Jupyter.

Responsabilidades

• 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.

Conhecimentos

Python

Scientific research

Data analysis

Code debugging

Formação académica

PhD/MD/Master with substantial research

Ferramentas

NumPy

pandas

SciPy

Matplotlib

scikit-learn

Jupyter

Descrição da oferta de emprego

• Role Title: Life Sciences Research Expert (Python)
• Role Type: Contractor (~15 hours per week)
• Location: Global, fully remote
• 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:

• 1. Medicine and biomedical science
• 2. Computational biology
• 4. Molecular and cellular biology
• 5. Biotechnology and bioinformatics
• 6. Genetics and genomics
• 7. Ecology and evolutionary biology
• 8. Biostatistics or biological data science

Scope of Work

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

Preferred Qualifications

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

Process

• 2. Complete an AI interview of approximately 30 minutes.
• 3. 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.

What You’ll Do

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