Senior Computational Biologist

Placements24; South Africa; À distance; ZAR 900 000 - 1 300 000; Plein temps

Avantages offerts par ce poste

Health insurance

Annual leave

Conferences & workshops

Professional development

Résumé du poste

Placements24 is seeking a Senior Computational Biologist for a forward-thinking genomic research company in Queenstown, Eastern Cape. You will develop and apply computational methods to large-scale genomic, transcriptomic, and proteomic datasets, collaborating with biologists and clinicians.

We require a PhD or Master’s in a quantitative field with 5+ years in computational biology, strong Python/R skills, Linux, and ML knowledge.

Qualifications

• Ph.D. or Master's in Computational Biology, Bioinformatics, CS, Statistics, Genetics, or related quantitative field.
• Minimum 5 years in computational biology or bioinformatics, with focus on large-scale datasets.
• Strong programming in Python and/or R; Biopython/Bioconductor experience.
• Proficiency with Linux/Unix and shell scripting.
• Solid understanding of statistical modeling, ML, and data mining.
• Experience with common bioinformatics tools/databases.
• Familiarity with NGS data analysis (variant calling, RNA-Seq) is desirable.
• Excellent analytical, problem-solving, and communication skills.
• Ability to manage multiple projects and deliver results in a multidisciplinary team.

Responsabilités

• Develop, maintain robust bioinformatics pipelines for diverse datasets (NGS).
• Design and run advanced statistical analyses and ML to identify patterns and biomarkers.
• Collaborate with experimental biologists, geneticists, and clinicians to interpret results.
• Contribute to experimental design and data collection strategies.
• Visualize complex data for presentations and publications.
• Stay current with advancements in computational biology and tools.
• Troubleshoot and optimize workflows; develop new methods.
• Mentor junior computational biologists and guide teams.
• Ensure data integrity, reproducibility, and efficient data management.
• Communicate complex findings clearly to technical and non-technical audiences.

Connaissances

Python

R

Bioinformatics

Linux/Unix

Statistics

Machine Learning

Communication

Formation

Ph.D. in Computational Biology

Master's in Bioinformatics

Outils

Biopython

Bioconductor

Shell scripting

Description du poste

About the Role

Our client, a forward-thinking genomic research company located in Queenstown, Eastern Cape , is actively seeking a Senior Computational Biologist to join their advanced analytics team. This role is central to interpreting and deriving insights from large-scale genomic, transcriptomic, and proteomic datasets. You will be responsible for developing and applying sophisticated computational methods, algorithms, and statistical models to drive biological discovery. The ideal candidate will possess a strong foundation in biology coupled with extensive expertise in bioinformatics, data science, and programming. This is a key position offering the opportunity to contribute to groundbreaking research in areas such as personalized medicine and disease genetics. We are committed to fostering a collaborative environment where scientific innovation thrives and data-driven insights are paramount. The successful applicant will work on challenging projects that push the boundaries of biological understanding and have a significant impact on healthcare. This role requires a deep passion for unraveling complex biological questions through computational approaches.

Key Responsibilities

• Develop, implement, and maintain robust bioinformatics pipelines for the analysis of diverse biological datasets, including next-generation sequencing (NGS).
• Design and execute advanced statistical analyses and machine learning algorithms to identify patterns, biomarkers, and relationships in biological data.
• Collaborate with experimental biologists, geneticists, and clinicians to interpret results and integrate computational findings with biological context.
• Contribute to the design of experiments and data collection strategies to maximize scientific output.
• Visualize complex biological data effectively for internal presentations and publications.
• Stay current with the latest advancements in computational biology, bioinformatics, genomics, and relevant software tools.
• Troubleshoot and optimize existing bioinformatics workflows and develop new methodologies.
• Mentor junior computational biologists and provide technical guidance to research teams.
• Ensure data integrity, reproducibility, and efficient management of large datasets.
• Communicate complex computational findings clearly and concisely to both technical and non-technical audiences.

Requirements

• Ph.D. or Master's degree in Computational Biology, Bioinformatics, Computer Science, Statistics, Genetics, or a related quantitative field.
• A minimum of 5 years of relevant experience in computational biology or bioinformatics, with a focus on analyzing large-scale biological datasets.
• Strong programming skills in Python and/or R, with experience in relevant bioinformatics libraries (e.g., Biopython, Bioconductor).
• Proficiency in working with Linux/Unix operating systems and shell scripting.
• Solid understanding of statistical modeling, machine learning techniques, and data mining principles.
• Experience with common bioinformatics tools and databases.
• Familiarity with next-generation sequencing data analysis (e.g., variant calling, RNA-Seq analysis) is highly desirable.
• Excellent analytical, problem-solving, and critical-thinking skills.
• Strong communication and collaboration skills, with the ability to work effectively in a multidisciplinary team.
• Demonstrated ability to manage multiple projects and deliver results in a timely manner.

Benefits

• An attractive annual salary between R and R , based on experience and qualifications.
• Comprehensive health insurance, including medical and dental coverage.
• Generous annual leave and company-mandated holidays.
• Opportunities for continuous professional development, including attending conferences and workshops.
• Access to high-performance computing resources and advanced software.
• A dynamic and collaborative research environment focused on innovation.
• Performance-based bonuses and recognition programs.
• Retirement savings plan with employer contributions.