Senior Computational Biologist

About the Role  Our client is seeking an experienced Senior Computational Biologist to join their innovative research team in Kimberley . This role is crucial for analyzing complex biological datasets, including genomics, transcriptomics, and proteomics, to uncover insights into disease mechanisms and therapeutic targets. You will develop and implement advanced computational and statistical methods, collaborate with experimental scientists, and contribute to the strategic direction of research projects.

This is an exceptional opportunity for a quantitative scientist to make a significant impact in a leading research environment.

Key Responsibilities   Develop, implement, and optimize computational pipelines for the analysis of large-scale biological data.
Apply statistical modeling and machine learning techniques to identify patterns, biomarkers, and drug targets.
Collaborate closely with experimental biologists to interpret results and design follow-up experiments.
Visualize and communicate complex biological data and findings to both technical and non-technical audiences.
Manage and curate biological databases, ensuring data integrity and accessibility.
Stay current with advancements in computational biology, bioinformatics, and relevant scientific fields.
Requirements   PhD in Computational Biology, Bioinformatics, Statistics, Computer Science, or a related quantitative field.
Minimum of 6 years of experience in computational biology or bioinformatics, with a focus on biological data analysis.
Proficiency in programming languages such as Python and R, and experience with relevant bioinformatics tools and databases.
Strong knowledge of statistical methods, machine learning algorithms, and their application to biological problems.

Experience with next-generation sequencing (NGS) data analysis is highly desirable.
Excellent communication, presentation, and teamwork skills.
Benefits   Highly competitive salary and performance-based bonus.
Comprehensive medical, dental, and vision insurance coverage.
Retirement fund contributions and generous paid time off.
Opportunities for attending scientific conferences and workshops.
Access to powerful computing resources and a collaborative research environment in Kimberley .
Flexible working arrangements to support a hybrid work model.

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