About Wulfstan Analytics

Wulfstan Analytics is a technology and research-focused company supporting international clients across healthcare, life sciences, biomedical research and data science.

We combine scientific expertise, data-driven methods and technology to help research teams interpret complex information and deliver high-quality analytical outputs.

As our work continues to expand, we are looking for a motivated Bioinformatician to contribute to biological data analysis and reproducible computational research.

About the Role

We are looking for a Bioinformatician to support the analysis and interpretation of genomic, transcriptomic, clinical and other biomedical datasets for healthcare, life sciences and research projects.

The ideal candidate should have strong computational biology skills, experience with bioinformatics tools and pipelines and the ability to communicate complex findings clearly and accurately.

Candidates should have 2 years of relevant experience in bioinformatics, computational biology or a related field, with the ability to work independently and collaboratively on research projects.

Key Responsibilities

• Analysis and quality control of genomic, transcriptomic, proteomic, and other high-throughput biological datasets.
• Develop, validate and maintain reproducible bioinformatics pipelines.
• Perform variant annotation, genetic association studies and pathway analysis as required.
• Integrate molecular, clinical and phenotypic data to support research and interpretation.
• Prepare visualizations, technical reports, research summaries and publication-ready outputs.
• Work with scientific, clinical, statistical and technical teams to define analysis requirements.
• Document workflows, code, parameters, reference data and quality-control results.

Required Qualifications and Skills

• Bachelor's degree in Bioinformatics, Computational Biology, Biotechnology, Molecular Biology, Genetics or a related field.
• Minimum 2 years of relevant experience in bioinformatics, computational biology or related research.
• Experience using Python, R, Bash, Linux and common bioinformatics tools.
• Understanding of molecular biology, genetics, genomics and next-generation sequencing workflows.
• Experience with biological databases, sequence formats, data quality control and visualization.
• Ability to write clear, reproducible and well-documented analytical code.
• Strong problem-solving skills and high attention to detail and accuracy.

Preferred Qualifications

• Experience with WGS/WES data, GWAS or other statistical genetics workflows.
• Familiarity with genetic variant annotation tools and resources, such as VEP, Ensembl, ClinVar or gnomAD.
• Familiarity with workflow orchestration tools such as Nextflow or Snakemake.
• Familiarity with containerization technologies such as Docker or Singularity/Apptainer.
• Knowledge of cloud or high-performance computing environments, Git and reproducible research practices.
• Familiarity with clinical or biomedical research, data privacy, scientific publications and manuscript preparation.

Ideal Candidate Profile

The ideal candidate is analytical, detail-oriented and experienced in computational biology. You should be comfortable working with biological data, learning new tools and communicating scientific findings clearly.

We welcome applications from professionals with at least 2 years of relevant experience, a strong academic foundation and a genuine interest in bioinformatics, genomics and biomedical research.

Application Instructions

Interested candidates with 2 years of relevant experience are encouraged to apply.