Computational Biology Expert

Micro1; India; A distancia; INR 1.200.000 - 2.100.000; A tiempo parcial

Descripción de la vacante

Cashback24x7 is seeking a Computational Biology Expert for a remote, contractor position. You will apply your expertise to train next-generation AI systems, shaping how models learn and reason through high-quality, real-world biological input.

You will evaluate AI outputs in genomics, transcriptomics, and systems biology use cases, and collaborate with interdisciplinary teams to provide actionable biological insights and improve pipelines. Strong communication skills are essential.

Formación

• PhD in Biology, Bioinformatics, or closely related field or equivalent industry/research experience.
• Proven experience in data-driven biological research and computational analysis workflows.
• Proficiency with scripting (Python, R, Bash) and tools.

Responsabilidades

• Leverage biology domain expertise to evaluate, annotate, and benchmark AI systems in real-world computational biology use cases.
• Assess accuracy, relevance, and performance of AI-generated outputs in genomics, transcriptomics, and systems biology scenarios.
• Apply analytical reasoning to review scientific workflows and pipelines, identifying strengths and areas for improvement.
• Collaborate with interdisciplinary teams, providing feedback on AI model performance based on biological context.
• Document observations and findings with clarity, highlighting scientific rationale and actionable insights.
• Communicate complex concepts to technical and non-technical stakeholders through written and verbal channels.
• Stay current on emerging trends in computational biology, bioinformatics, and machine learning in biology.

Conocimientos

Python

R

Bash

Genomics

Bioinformatics

Educación

PhD in Biology or Bioinformatics

Herramientas

BWA

GATK

STAR

Salmon

Seurat

Scanpy

Descripción del empleo

Job Title: Computational Biology Expert

Job Type: Contractor

Location: Remote

Job Summary

In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input.

Key Responsibilities

• Leverage your biology domain expertise to evaluate, annotate, and benchmark AI systems in real-world computational biology use cases.
• Assess the accuracy, relevance, and performance of AI-generated outputs in genomics, transcriptomics, and systems biology scenarios.
• Apply advanced analytical reasoning to critically review scientific workflows and pipelines, identifying strengths and areas for improvement.
• Collaborate with interdisciplinary teams, providing feedback on AI model performance based on biological context.
• Document observations and findings with clarity, highlighting scientific rationale and actionable insights.
• Communicate complex concepts effectively through both written and verbal channels to technical and non-technical stakeholders.
• Stay current on emerging trends in computational biology, bioinformatics, and machine learning in biology.

Required Skills and Qualifications

• PhD in Biology, Bioinformatics, or a closely related field, or equivalent industry/research experience.
• Proven experience in data-driven biological research and computational analysis workflows.
• Proficiency with scripting (Python, R, Bash) and scientific tools such as BWA, GATK, STAR, Salmon, Seurat, or Scanpy would be ideal.
• Deep understanding of genomics, transcriptomics, structural biology, or systems biology is desirable.
• Excellent scientific reasoning, analytical, and problem-solving abilities.
• Strong written and verbal communication skills, with the ability to articulate findings and collaborate effectively.
• Comfort working remotely and contributing to distributed teams.

Preferred Qualifications

• Experience with AI/ML or LLM evaluation in a biology context.
• Hands-on experience with NGS pipelines, CRISPR workflows, AlphaFold, or PyMOL.
• Published research or contributions to open-source projects in computational biology or bioinformatics.