Remote Computational Biologist: Drug Discovery Impact

Placements24; Siyancuma Local Municipality; Hybrid; ZAR 1,796,000 - 2,449,000; Full time

Benefits offered by this job

Bonus potential

Health, dental, and vision insurance

Stock options

Flexible remote work

Impactful research opportunities

Job summary

Placements24 is seeking a highly skilled Computational Biologist to join a remote Drug Discovery team. You will analyze complex biological data, develop predictive models, and guide experimental design in a collaborative, flexible remote setting.

The ideal candidate will apply computational methods to biological problems, working closely with biologists, chemists, and data scientists to accelerate therapeutic research.

Qualifications

• PhD in Computational Biology, Bioinformatics, CS, or related field.
• At least 4 years of experience in computational biology or bioinformatics.
• Proficiency in Python or R and libraries like pandas, NumPy, SciPy.
• Experience with chemoinformatics and structure-based drug design tools.
• Experience with ML frameworks (TensorFlow, PyTorch) and statistical modeling.
• Excellent communication and collaboration for remote teamwork.

Responsibilities

• Design computational strategies for HTS, omics, and clinical data.
• Develop ML models for target ID, lead optimization, and efficacy/toxicity.
• Collaborate with medicinal chemists on drug candidate design using SBDD.
• Build and maintain biological databases and knowledge graphs.
• Visualize and interpret complex datasets to generate actionable insights.
• Stay updated on advances in computational biology and drug discovery.

Skills

Python

R

Machine learning

Chemoinformatics

Structure-based drug design

Communication

Remote collaboration

Education

PhD in Computational Biology or related field

Tools

TensorFlow

PyTorch

Pandas

NumPy

SciPy

Job description

Placements24 is seeking a highly skilled Computational Biologist to join a remote Drug Discovery team. You will analyze complex biological data, develop predictive models, and guide experimental design in a collaborative, flexible remote setting.

The ideal candidate will apply computational methods to biological problems, working closely with biologists, chemists, and data scientists to accelerate therapeutic research.