Bioinformatics Python Pro — Part-time AI Problem Designer

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Kuwait City

On-site

KWD 8,900 - 15,000

Part time

10 days ago
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Job summary

Mindrift connects specialists with project-based AI opportunities for leading tech companies, focusing on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment.

This role suits biology specialists with Python experience and is open to part-time, non-permanent projects. Projects typically run 10–20 hours per week during active phases, with compensation up to $35 per hour, depending on level and contribution pace.

Qualifications

  • Degree in biology or related field.
  • Python proficiency for numerical validation.
  • 2+ years of professional experience in applied, research, or teaching roles.
  • Experience with biological data analysis and algorithms.
  • Familiarity with bioinformatics tools and computational methods.

Responsibilities

  • Design computational biology problems that simulate real biology research workflows.
  • Create Python-based problems requiring numerical validation.
  • Ensure problems are computationally intensive and non-manual.
  • Develop problems needing non-trivial reasoning in bioinformatics.
  • Base problems on real research challenges from biology practice.
  • Verify solutions using Python with standard scientific libraries.
  • Document problem statements clearly and provide verified answers.

Skills

Biology background
Python programming
Bioinformatics
Data analysis

Education

Degree in biology

Tools

NumPy
Pandas
SciPy
BioPython
MATLAB
R
SQL

Job description

Mindrift connects specialists with project-based AI opportunities for leading tech companies, focusing on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment.

This role suits biology specialists with Python experience and is open to part-time, non-permanent projects. Projects typically run 10–20 hours per week during active phases, with compensation up to $35 per hour, depending on level and contribution pace.

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