Senior Bioinformatician

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

Benefits offered by this job

Salary bonus

Health benefits

Professional development

Hybrid work

Collaborative research

Job summary

Placements24 in Vereeniging is seeking a Senior Bioinformatician to analyze large-scale biological data, including genomic, transcriptomic, and epigenomic datasets, to support drug discovery and development.

You will develop computational pipelines, apply statistical analyses, and build visualization tools, collaborating across disciplines in a hybrid work environment.

Qualifications

• M.Sc. or Ph.D. in Bioinformatics, Computational Biology, Statistics, Computer Science, or related quantitative field.
• Minimum of 4 years of hands-on bioinformatics analysis with genomic/transcriptomic data.
• Proficiency in Python, R, or Perl and experience with bioinformatics tools and databases.
• Strong understanding of statistics, machine learning, and data mining techniques.
• Experience with cloud computing and/or HPC clusters.
• Excellent communication and teamwork in a hybrid setting.

Responsibilities

• Develop, optimize, and maintain bioinformatics pipelines for high-throughput sequencing data.
• Perform statistical analysis to identify trends, biomarkers, and targets.
• Collaborate with experimental biologists and computational scientists to interpret data.
• Design algorithms for data mining, pattern recognition, and predictive modeling.
• Visualize complex data for clear communication to scientific audiences.
• Contribute to experimental design and interpretation of results.

Skills

Python

R

Perl

Statistics

Machine learning

Data mining

Hybrid collaboration

Education

M.Sc. or Ph.D. in Bioinformatics/Computational Biology/Statistics/CS

Tools

Bioinformatics tools

Databases

Job description

About the Role

Our client is looking for an experienced Senior Bioinformatician to join their growing team in Vereeniging. This role will focus on the analysis of large-scale biological datasets, including genomic, transcriptomic, and epigenomic data, to support drug discovery and development efforts. You will play a key role in developing and implementing computational pipelines, statistical analyses, and visualization tools to extract meaningful insights from complex data. The position requires a blend of strong computational skills, biological understanding, and the ability to collaborate effectively within a hybrid work environment, contributing to cutting-edge research.

Key Responsibilities

• Develop, optimize, and maintain bioinformatics pipelines for processing and analyzing high-throughput sequencing data.
• Perform statistical analysis of complex biological datasets to identify key trends, biomarkers, and potential therapeutic targets.
• Collaborate with experimental biologists and computational scientists to interpret data and generate actionable insights.
• Design and implement algorithms for data mining, pattern recognition, and predictive modeling.
• Visualize complex data effectively for clear communication to scientific audiences.
• Contribute to the design of experiments and the interpretation of results in the context of biological questions.

Requirements

• M.Sc. or Ph.D. in Bioinformatics, Computational Biology, Statistics, Computer Science, or a related quantitative field.
• Minimum of 4 years of hands-on experience in bioinformatics analysis, particularly with genomic and transcriptomic data.
• Proficiency in programming languages such as Python, R, or Perl, and experience with relevant bioinformatics tools and databases.
• Strong understanding of statistical methods, machine learning, and data mining techniques.
• Experience with cloud computing platforms and/or high-performance computing clusters.
• Excellent communication and teamwork skills, with the ability to work effectively in a hybrid setting.

Benefits

• Competitive salary and performance-related bonus opportunities.
• Comprehensive health, dental, and retirement benefits.
• Support for professional development, including conference attendance and training.
• Hybrid work arrangement promoting work-life balance.
• Collaborative research environment focused on scientific innovation.