Senior Computational Biologist

Placements24; Mbombela (Nelspruit); Hybrid; ZAR 2,000,000 - 3,000,000; Full time

Benefits offered by this job

Competitive salary

Remote-first environment

Health insurance

Job summary

Placements24 is seeking a Senior Computational Biologist to join a remote-first team focused on high-impact biological data analysis. You will drive insights from genomics, transcriptomics, proteomics, and clinical data, designing models and tools to identify therapeutic targets.

You will collaborate with biologists, bioinformaticians, and data scientists to translate results into actionable research directions, while staying current with advances in the field in a flexible, remote environment.

Qualifications

• Ph.D. in a quantitative field related to computational biology.
• Minimum 5 years of experience in computational biology or bioinformatics.
• Proficiency in Python and R; experience with scikit-learn and Bioconductor.
• Experience with high-performance computing environments and cloud platforms.

Responsibilities

• Develop and apply advanced computational and statistical methods to analyze large-scale biological datasets.
• Integrate multi-omics data to identify pathways, biomarkers, and therapeutic targets.
• Design and implement machine learning models for predictive biology and drug discovery.
• Collaborate with experimental teams to interpret results and guide research hypotheses.
• Develop custom software tools and pipelines to support data analysis and visualization needs.
• Stay current with the latest advancements in computational biology, bioinformatics, and related domains.

Skills

Python

R

Machine learning

Biostatistics

Education

PhD in Computational Biology / Bioinformatics

Tools

scikit-learn

Bioconductor

HPC

Cloud platforms

Job description

About the Role

Our client is seeking a talented Senior Computational Biologist for a fully remote position, to drive insights from complex biological datasets. This role is crucial for integrating and analyzing diverse data types, including genomics, transcriptomics, proteomics, and clinical data, to uncover novel biological mechanisms and identify potential therapeutic targets. You will work closely with experimental biologists, bioinformaticians, and data scientists to develop sophisticated analytical strategies and translate findings into actionable research directions. This is a fantastic opportunity to contribute to groundbreaking research in a flexible, remote-first environment.

Key Responsibilities

• Develop and apply advanced computational and statistical methods to analyze large-scale biological datasets.
• Integrate multi-omics data to identify key pathways, biomarkers, and therapeutic targets.
• Design and implement machine learning models for predictive biology and drug discovery.
• Collaborate with experimental teams to interpret results and guide research hypotheses.
• Develop custom software tools and pipelines to support data analysis and visualization needs.
• Stay current with the latest advancements in computational biology, bioinformatics, and relevant biological domains.

Requirements

• Ph.D. in Computational Biology, Bioinformatics, Statistics, Computer Science, or a related quantitative field.
• Minimum of 5 years of experience in computational biology or bioinformatics, with a strong focus on biological data analysis.
• Proficiency in programming languages such as Python and R, and experience with relevant libraries (e.g., scikit-learn, Bioconductor).
• Experience with high-performance computing environments and cloud platforms.
• Strong understanding of molecular biology, genetics, and disease mechanisms.
• Excellent communication and collaboration skills, with proven ability to work effectively in a remote team.

Benefits

• Highly competitive salary and remote work flexibility.
• Comprehensive health, dental, and vision insurance.
• Generous allowance for home office setup and continuous professional development.
• Opportunity to work on high-impact research at the intersection of biology and computation.
• Access to cutting-edge computational infrastructure and diverse biological datasets.