Senior Computational Biologist

Placements24; Soweto; Hybrid; ZAR 900,000 - 1,300,000; Full time

Benefits offered by this job

Competitive salary

Home office allowance

Flexible hours

Professional growth

Remote-friendly culture

Job summary

Placements24 is seeking a Senior Computational Biologist to join a fully remote, innovative research team focused on precision medicine and therapeutic development. You will design and implement computational pipelines and apply machine learning to large-scale genomics and clinical datasets.

Working with biologists, data scientists, and clinicians worldwide, you will translate complex data into actionable strategies and mentorship for junior team members in a remote environment.

Qualifications

• PhD in Computational Biology, Bioinformatics, Statistics, CS, or related field.
• Minimum of 5 years of experience in computational biology or bioinformatics research.
• Proficiency in Python or R and related bioinformatics libraries/tools.
• Strong background in statistical modeling, ML, and data mining.
• Experience analyzing large-scale biological data including NGS.
• Excellent written and verbal communication for remote collaboration.

Responsibilities

• Design and implement computational pipelines for diverse biological datasets.
• Develop and apply ML models to identify biomarkers and targets.
• Collaborate with biologists to integrate findings in biological context.
• Interpret results and communicate key findings to technical and non-technical audiences.
• Contribute to experimental design and research strategy.
• Mentor junior computational biologists and grow team expertise.

Skills

Statistical modeling

Machine learning

Remote collaboration

Scientific communication

Education

PhD in Computational Biology/Bioinformatics

Tools

Python

R

NGS data analysis tools

Job description

About the Role

Our client is seeking a seasoned Senior Computational Biologist to join their fully remote, innovative research team. This role is central to leveraging large-scale biological data to drive breakthroughs in precision medicine and therapeutic development. You will be responsible for developing and applying advanced computational and statistical methods to analyze complex datasets, including genomics, transcriptomics, and clinical data. Working collaboratively with a global team of biologists, data scientists, and clinicians, you will translate data-driven insights into actionable strategies for patient care. This is an exceptional opportunity for a dedicated professional to make a significant impact on scientific discovery from a remote setting.

Key Responsibilities

• Design and implement computational pipelines for the analysis of diverse biological datasets (genomic, transcriptomic, proteomic, etc.).
• Develop and apply statistical and machine learning models to identify disease biomarkers and therapeutic targets.
• Collaborate with experimental biologists to integrate computational findings with biological context.
• Interpret complex results and communicate key findings effectively to both technical and non-technical audiences.
• Contribute to the design of experiments and the strategic direction of research projects.
• Mentor junior computational biologists and contribute to the team's scientific expertise.

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 research.
• Expertise in programming languages such as Python or R, and experience with relevant bioinformatics tools and libraries.
• Strong understanding of statistical modeling, machine learning, and data mining techniques.
• Experience analyzing large-scale biological data, including next-generation sequencing data.
• Excellent communication and collaboration skills, with a proven ability to excel in a remote work environment.

Benefits

• Highly competitive salary and bonus structure.
• Comprehensive health, dental, and vision insurance.
• Generous allowance for home office setup and technology.
• Flexible working hours and a focus on work-life balance.
• Opportunities for continuous learning and professional growth in a leading research organization.