Senior Computational Biologist - Drug Discovery

Placements24; Stellenbosch; Hybrid; ZAR 1,959,000 - 2,938,000; Full time

Benefits offered by this job

Stock options

Home office budget

Remote work stipend

Professional development

Job summary

Placements24 is seeking a highly accomplished Senior Computational Biologist to lead data analytics and modeling for drug discovery. This fully remote role offers the chance to work with a world-class research team from anywhere.

You will analyze genomics, transcriptomics, and proteomics data, build predictive models for drug response, and collaborate with bench scientists to translate findings into preclinical strategies.

Qualifications

• PhD in Computational Biology, Biostatistics or related field.
• 7+ years of experience in computational biology, with a track record in drug discovery or related areas.
• Proficiency in Python or R and experience with bioinformatics libraries/tools.

Responsibilities

• Develop and apply advanced computational and statistical methods to analyze complex biological datasets (genomics, transcriptomics, proteomics).
• Identify and validate novel drug targets and biomarkers using integrated data analysis approaches.
• Build predictive models for drug response, efficacy, and toxicity based on preclinical and clinical data.
• Collaborate closely with bench biologists, chemists, and clinicians to translate computational findings into actionable research strategies.
• Design and implement bioinformatics pipelines for data processing and analysis, ensuring reproducibility and scalability.
• Stay current with the latest advancements in computational biology, bioinformatics, and drug discovery technologies.

Skills

Python

R

Machine learning

Biostatistics

Data analysis

Remote collaboration

Education

PhD in Computational Biology

Tools

Bioinformatics tools

Job description

About the Role

Our client is seeking a highly accomplished Senior Computational Biologist to drive innovation in drug discovery through advanced data analytics and modeling. This is a fully remote position, offering flexibility and the opportunity to work with a world-class research team from anywhere. You will leverage large biological datasets, including genomics, transcriptomics, and proteomics, to identify novel therapeutic targets, predict drug efficacy, and optimize preclinical development strategies. This role is critical for advancing our client's pipeline and requires a deep understanding of biological systems and sophisticated computational approaches.

Key Responsibilities

• Develop and apply advanced computational and statistical methods to analyze complex biological datasets (genomics, transcriptomics, proteomics).


• Identify and validate novel drug targets and biomarkers using integrated data analysis approaches.


• Build predictive models for drug response, efficacy, and toxicity based on preclinical and clinical data.


• Collaborate closely with bench biologists, chemists, and clinicians to translate computational findings into actionable research strategies.


• Design and implement bioinformatics pipelines for data processing and analysis, ensuring reproducibility and scalability.


• Stay current with the latest advancements in computational biology, bioinformatics, and drug discovery technologies.

Requirements

• Ph.D. in Computational Biology, Bioinformatics, Biostatistics, or a related quantitative field.


• Minimum of 7 years of experience in computational biology, with a proven track record in drug discovery or related areas.


• Expertise in programming languages such as Python or R, and experience with bioinformatics libraries and tools.


• Strong understanding of molecular biology, genetics, and disease mechanisms.


• Experience with machine learning techniques applied to biological data.


• Excellent communication and collaboration skills, essential for a remote work environment.

Benefits

• Highly competitive salary and stock options package.


• Comprehensive health, dental, and vision insurance coverage.


• Generous home office setup budget and remote work stipends.


• Significant opportunities for professional development and scientific contribution.


• Work from home flexibility, allowing for a strong work-life balance.