Lead Computational Biologist

Placements24; Randfontein; Hybrid; ZAR 1,200,000 - 2,000,000; Full time

Benefits offered by this job

Hybrid work arrangements

Professional development opportunities

Access to high-performance computing

Job summary

Placements24 is seeking a Lead Computational Biologist to join our research team in Rustenburg. The role focuses on developing and applying advanced computational approaches to analyze large-scale omics data and identify novel drug targets.

You will guide a team of bioinformaticians, collaborate with experimental scientists, and translate complex results into actionable insights, while contributing to publications and grant proposals.

Qualifications

• Ph.D. or M.S. in a quantitative field.
• 6+ years in computational biology or bioinformatics, with ≥2 years in leadership.
• Proficiency in Python or R and bioinformatics libraries/tools.
• Strong experience with WGS, RNA-Seq analyses.
• Solid understanding of statistics and ML methods.

Responsibilities

• Lead development of advanced bioinformatics pipelines for large-scale omics data.
• Identify biomarkers, therapeutic targets, and disease mechanisms.
• Collaborate with experimental teams to interpret results and guide research directions.
• Develop and maintain scalable computational infrastructure and workflows.
• Mentor and manage a team of computational biologists and bioinformaticians.
• Present findings to leadership and contribute to publications and grant applications.

Skills

Leadership

Python

R

Bioinformatics

Communication

Education

Ph.D. in Bioinformatics/Computational Biology/CS or related

M.S. in Bioinformatics/Computational Biology or related

Tools

Python libraries

R/Bioconductor

NGS analysis tools

Job description

About the Role

Our client is actively recruiting a highly skilled Lead Computational Biologist to join their dynamic research team in Rustenburg . This leadership position will involve developing and applying cutting-edge computational approaches to analyze large-scale biological datasets, including genomics, transcriptomics, and proteomics. You will play a crucial role in identifying novel targets for drug development and understanding complex biological systems. The ideal candidate will have a strong background in bioinformatics, a passion for data-driven discovery, and the ability to lead a team of talented bioinformaticians. This role offers the chance to work on challenging projects at the intersection of biology and computer science, contributing to significant advancements in the pharmaceutical industry. You will collaborate closely with experimental biologists and data scientists to translate complex data into actionable insights.

Key Responsibilities

• Lead the development and implementation of advanced bioinformatics pipelines for the analysis of large-scale omics data.
• Design and conduct computational studies to identify biomarkers, therapeutic targets, and disease mechanisms.
• Collaborate with experimental teams to interpret results and guide future research directions.
• Develop and maintain scalable computational infrastructure and workflows.
• Mentor and manage a team of computational biologists and bioinformaticians.
• Present findings to scientific leadership and contribute to publications and grant applications for the Rustenburg site.

Requirements

• Ph.D. or M.S. in Bioinformatics, Computational Biology, Computer Science, or a related quantitative field.
• Minimum of 6 years of experience in computational biology or bioinformatics, with at least 2 years in a leadership role.
• Expertise in programming languages such as Python or R, and proficiency with relevant bioinformatics libraries and tools.
• Strong experience with analyzing next-generation sequencing data (e.g., WGS, RNA-Seq).
• Solid understanding of statistical methods, machine learning algorithms, and database management.
• Excellent communication and collaboration skills, with the ability to explain complex computational concepts to non-experts in Rustenburg .

Benefits

• A competitive salary and comprehensive benefits package.
• Opportunities to lead impactful projects in a cutting-edge research environment.
• Access to high-performance computing resources and extensive datasets.
• Professional development opportunities, including advanced training and conference attendance.
• Collaborative and innovative work culture focused on scientific advancement.
• Potential for hybrid work arrangements to support work-life balance.