Senior Research Scientist - Computational Biology

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

Benefits offered by this job

Remote work stipend

Health insurance

Professional development

Job summary

Placements24 is seeking a Senior Research Scientist in Computational Biology to lead advanced computational analyses from a remote setup. You will develop and apply methods to analyze genomic, transcriptomic, and proteomic data, driving discovery of disease mechanisms and targets.

Ideal candidates have a PhD and a strong publication record, with expertise in Python/R, ML, and cloud deployment. The role offers generous remote stipends and ongoing professional development within a globally

Qualifications

• PhD in Computational Biology, Bioinformatics, CS or related quantitative field.
• 5+ years in computational biology with strong publication record.
• Proficiency in Python or R and bioinformatics libraries.

Responsibilities

• Design and implement bioinformatics pipelines for omics data.
• Develop predictive models for drug targets and biomarkers.
• Collaborate with clinicians to interpret findings and guide experiments.
• Publish findings and present at conferences.
• Mentor junior researchers and contribute to strategy.

Skills

Python

R

Machine learning

Bioinformatics

Genomics

Cloud computing

Docker

Communication

Education

PhD in Computational Biology or related

Tools

Docker

AWS

GCP

Job description

About the Role

Our client is seeking a highly motivated and experienced Senior Research Scientist specializing in Computational Biology to join their innovative research team. This fully remote position offers the opportunity to drive cutting-edge research from the comfort of your own workspace. You will be instrumental in developing and applying advanced computational methods to analyze complex biological data, contributing significantly to our understanding of disease mechanisms and the discovery of novel therapeutic targets. This role requires a deep scientific curiosity, a passion for data-driven insights, and the ability to collaborate effectively within a geographically dispersed team, fostering a culture of scientific excellence and shared discovery.

Key Responsibilities

• Design and implement sophisticated bioinformatics pipelines for the analysis of large-scale genomic, transcriptomic, and proteomic data.
• Develop and validate predictive models using machine learning and statistical techniques to identify potential drug targets and biomarkers.
• Collaborate with experimental biologists and clinicians to interpret research findings and guide future experimental design.
• Stay abreast of the latest advancements in computational biology, bioinformatics tools, and relevant biological fields.
• Author high-quality scientific publications and present findings at international conferences.
• Mentor junior researchers and contribute to the overall scientific strategy of the research group.

Requirements

• Ph.D. in Computational Biology, Bioinformatics, Computer Science, or a related quantitative field.
• Proven track record of at least 5 years in computational biology research, with a strong publication record.
• Expertise in programming languages such as Python or R, and experience with relevant bioinformatics libraries and frameworks.
• Proficiency in handling and analyzing diverse biological datasets, including next-generation sequencing data.
• Experience with cloud computing platforms (e.g., AWS, GCP) and containerization technologies (e.g., Docker).
• Excellent communication, presentation, and collaboration skills, essential for a remote team environment.

Benefits

• Competitive salary package commensurate with experience.
• Generous remote work stipend to support your home office setup.
• Comprehensive health, dental, and vision insurance plans.
• Opportunities for professional development, including conference attendance and training.
• A dynamic and intellectually stimulating remote work environment that values innovation and scientific rigor.
• Flexible working hours to accommodate work-life balance.