Computational Biologist - Bioinformatics

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

Benefits offered by this job

Hybrid work model

Comprehensive medical aid

Retirement fund contributions

Career development opportunities

Job summary

Placements24 is seeking a skilled Computational Biologist to join our Scientific Research & Development team in Cape Town. The role focuses on analyzing large-scale omics data, building predictive models, and translating findings into actionable hypotheses for drug discovery.

You will collaborate with experimental biologists and data scientists, design bioinformatics pipelines, and contribute to data visualization and knowledge management while enjoying a hybrid work arrangement blending remote

Qualifications

• MSc or PhD in Computational Biology, Bioinformatics, CS, Statistics, or related field.
• Proven experience analyzing large biological datasets (genomics, transcriptomics, proteomics).
• Proficiency in Python or R and bioinformatics libraries such as Biopython or Bioconductor.
• Familiarity with Unix/Linux environments and workflow systems (Snakemake, Nextflow).
• Experience with SQL and Git; strong analytical and communication skills.

Responsibilities

• Develop and implement bioinformatics pipelines for high-throughput sequencing data.
• Design and run statistical analyses and ML models to identify biomarkers and targets.
• Collaborate with wet-lab scientists to design experiments and interpret results.
• Visualize complex data and contribute to internal databases and knowledge management.
• Stay updated on advances in computational biology and tools.

Skills

Python

R

SQL

Git

Unix/Linux

Data visualization

Communication

Education

MSc or PhD in Computational Biology

Tools

Biopython

Bioconductor

Snakemake

Nextflow

Git

Job description

About the Role

Our client is seeking a skilled Computational Biologist to join their innovative Scientific Research & Development division in Cape Town . This role is crucial for analyzing large-scale biological data, developing predictive models, and driving insights that underpin our drug discovery and development pipelines. You will collaborate closely with experimental biologists and data scientists to translate complex genomic, proteomic, and transcriptomic data into actionable biological hypotheses. This hybrid role offers the flexibility of remote work combined with essential on-site collaboration, making it ideal for an individual who thrives in both independent research and team-based problem-solving within a vibrant scientific community.

Key Responsibilities

• Develop and implement bioinformatics pipelines for the analysis of high-throughput sequencing data (e.g., WGS, RNA-Seq, ChIP-Seq).
• Design and execute statistical analyses and machine learning models to identify novel biomarkers and therapeutic targets.
• Collaborate with wet-lab scientists to design experiments and interpret results from a computational perspective.
• Visualize complex biological data in an intuitive and informative manner.
• Contribute to the development of internal databases and knowledge management systems for biological data.
• Stay abreast of the latest advancements in computational biology and bioinformatics tools and methodologies.

Requirements

• MSc or Ph.D. in Computational Biology , Bioinformatics, Computer Science, Statistics, or a related quantitative field.
• Proven experience in analyzing large biological datasets, with a strong understanding of genomics, transcriptomics, or proteomics.
• Proficiency in programming languages such as Python or R, and experience with relevant bioinformatics libraries (e.g., Biopython, Bioconductor).
• Familiarity with Unix/Linux environments and workflow management systems (e.g., Snakemake, Nextflow).
• Experiencewith database querying languages (e.g., SQL)andversion control systems (e.g., Git).
• Strong analytical and problem-solving skills, with the ability to communicate technical findings to non-technical audiences.

Benefits

• Competitive salary package commensurate with experience.
• Comprehensive medical aidand retirement fund contributions.
• Hybrid work model offering flexibility between remote and in-office work.
• Access to state-of-the----‑-ainsulations‑‑
• Opportunities for career growth and professional development through training and conference participation.
• Engage in cutting-edge research that contributes to significant health advancements.