Computational Biologist - Genomics

Placements24; Randburg; Híbrido; ZAR 1.100.000 - 1.700.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Hybrid work in Randburg

Professional development

Descripción de la vacante

Placements24 in Randburg is seeking a Computational Biologist to join its advanced genomics research group. The role focuses on analyzing large-scale genomic and transcriptomic datasets to uncover biological insights and drive discoveries in disease mechanisms and drug development.

You will develop and apply bioinformatics tools and pipelines and collaborate with experimental biologists. The ideal candidate holds a Ph.D.

Formación

• Ph.D. or MSc in Computational Biology, Bioinformatics, Statistics, CS or related quantitative field.
• Proven experience analyzing next-generation sequencing (NGS) data.
• Proficiency in programming languages such as Python, R, or Perl, and experience with bioinformatics tools and databases.
• Strong understanding of statistical methods and machine learning techniques applied to biological data.
• Experience with high-performance computing environments and cloud computing platforms.
• Excellent communication and collaboration skills in a multidisciplinary team.

Responsabilidades

• Develop and implement bioinformatics pipelines for genomic, transcriptomic, and proteomic data.
• Perform statistical analysis to identify patterns and generate hypotheses from large datasets.
• Collaborate with experimental biologists to design studies and interpret results.
• Build predictive models and algorithms to address biological questions.
• Visualize complex biological data for accessible interpretation.
• Contribute to scientific publications and presentations.

Conocimientos

Python

R

Perl

Statistics

Machine learning

HPC

Cloud computing

Communication

Collaboration

Educación

Ph.D. or MSc in Computational Biology

Herramientas

NGS tools

Bioinformatics pipelines

Descripción del empleo

About the Role

Our client is seeking a skilled Computational Biologist to join their advanced genomics research group in Randburg . This role is crucial for analyzing large-scale genomic and transcriptomic datasets to uncover biological insights and drive discoveries in areas such as disease mechanisms and drug development. You will develop and apply sophisticated bioinformatics tools and pipelines, collaborate with experimental biologists, and contribute to high-impact research publications. The ideal candidate possesses a strong quantitative background, expertise in programming and statistical analysis, and a passion for leveraging big data to unravel complex biological questions in a dynamic research environment.

Key Responsibilities

• Develop and implement bioinformatics pipelines for the analysis of genomic , transcriptomic, and proteomic data.
• Perform statistical analysis and interpretation of large biological datasets to identify patterns and generate hypotheses.
• Collaborate closely with experimental biologists to design studies and interpret results.
• Build predictive models and develop algorithms to address specific biological questions.
• Visualize complex biological data in an accessible and informative manner.
• Contribute to scientific publications and presentations, sharing research findings with the broader scientific community.

Requirements

• Ph.D. or M.Sc. in Computational Biology, Bioinformatics, Statistics, Computer Science, or a related quantitative field.
• Proven experience in analyzing next-generation sequencing (NGS) data.
• Proficiency in programming languages such as Python, R, or Perl, and experience with relevant bioinformatics tools and databases.
• Strong understanding of statistical methods and machine learning techniques applied to biological data.
• Experience with high-performance computing environments and cloud computing platforms.
• Excellent communication and collaboration skills, with the ability to work effectively in a multidisciplinary team.

Benefits

• Competitive salary and benefits package.
• Opportunity to work on cutting-edge genomics research projects.
• Access to powerful computational resources and advanced analytical tools.
• Professional development support, including training and conference attendance.
• Hybrid work arrangement offering flexibility for remote and on-site collaboration in Randburg .