Computational Bioscience Expert (Python)
micro1
At a glance
Computational Bioscience Expert (Python) is a remote other opening at micro1. The posting places it in Global, fully remote. The post date on the listing is 7 Nov 2026. No deadline is filled in on the listing. The notes below are written by Akazi. The advertisement under them is the employer's own text.
- Company
- micro1
- Job type
- Other · Remote
- Location
- Global, fully remote
- Deadline
- Deadline not listed
- Date posted
- 7 Nov 2026
How to apply
- Computational Bioscience Expert (Python) is listed here so you can find it. micro1 takes the application. Akazi does not.
- Use Apply. It opens the employer's own site. Finish every step there, including an account if they ask for one.
- No deadline is stored in the listing fields. Read the advert in case the date is only written in the text, and apply while it is still open.
- It is remote (Global, fully remote). Say that you are based in Rwanda, which hours you can overlap with the team, and which languages you work in.
- Shape your CV around this other role and put the experience they ask for near the top. Name Kinyarwanda, English, or French only at the level you can actually work in.
- Do not pay a fee, buy a starter kit, or share a mobile-money PIN. A real application to micro1 will not ask you to pay in order to be hired.
Writing a CV for Rwanda · Preparing for interviews · Remote work from Rwanda
Apply(opens in a new tab)Employer advertisement
The text below is the public posting from micro1. Akazi did not write it.
Role Title : Computational Bioscience Expert (Python)
Pay: $60–$120/hour
Location : Global, fully remote
Job Type : Contractor (~15 hours per week)
Schedule: Flexible—you choose the hours and days you work, including weekends if desired
micro1 is seeking experienced Computational Bioscience Expert 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.
Scope of Work
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.
Preferred Qualifications
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.
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.
View the original posting(opens in a new tab)
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