Bioinformatics Scientist

Oxford - UK

Yearly Salary: £ 55000 - 75000

Experience Required: 4-5years

Posted on: 30+ days ago

Vacancies: 1 Vacancy

Job Summary

Our clients are hiring a results-driven Bioinformatics Analyst to contribute to high-impact biomedical research projects by analysing complex genomic and multi-omics data. The ideal candidate will have a strong foundation in biological data science programming and algorithmic thinking along with experience working in a cross-functional life sciences or healthcare setting.

Process analyse and interpret large-scale datasets including genomic transcriptomics proteomic and clinical data.
Perform data integration and pipeline development using scripting languages like Python R or Perl.
Develop and optimize bioinformatics workflows for sequencing data (e.g. RNA-seq WES WGS).
Use tools such as GATK Bioconductor BWA SAMtools and other NGS pipelines.
Collaborate with biologists clinicians and data scientists to generate actionable insights.
Maintain detailed documentation and ensure data analysis meets reproducibility standards.
Contribute to publications reports and presentations for internal and external stakeholders.

Requirements

Proven experience in bioinformatics analysis of high-throughput sequencing data (e.g. NGS).
Proficiency with Python R and command-line tools in Linux/Unix environments.
Familiarity with cloud platforms (e.g. AWS Google Cloud) and HPC environments.
Strong understanding of molecular biology genetics and biostatistics.
Excellent problem-solving skills and attention to detail.
Strong written and verbal communication skills to support collaborative research.

Desired Skills:

Experience with machine learning applications in bioinformatics.
Background in single-cell RNA sequencing epigenomics or meta-genomics.
Knowledge of FAIR data principles and version control systems (e.g. Git).
Understanding of clinical bioinformatics and regulatory-compliant environments.

Benefits

Competitive salary and annual performance bonus
Hybrid working model with flexible hours
Private healthcare and dental cover
Generous annual leave and training budget
Access to cutting-edge tools and industry-leading biotech partners

Required Skills:

Required Skills Strong proficiency in CRISPR/Cas9 genome editing Molecular cloning PCR gel electrophoresis and sequencing Experience working with mammalian and bacterial cell lines Familiarity with LIMS and laboratory data management tools Excellent documentation and scientific communication skills Desired Skills PhD or MSc in Genetics Molecular Biology or Biomedical Engineering Experience in bioinformatics tools (e.g. BLAST Geneious Benchling) Knowledge of synthetic biology or mRNA therapeutics Published peer-reviewed scientific research in the field

Process analyse and interpret large-scale datasets including genomic transcriptomics proteomic and clinical data.
Perform data integration and pipeline development using scripting languages like Python R or Perl.
Develop and optimize bioinformatics workflows for sequencing data (e.g. RNA-seq WES WGS).
Use tools such as GATK Bioconductor BWA SAMtools and other NGS pipelines.
Collaborate with biologists clinicians and data scientists to generate actionable insights.
Maintain detailed documentation and ensure data analysis meets reproducibility standards.
Contribute to publications reports and presentations for internal and external stakeholders.

Requirements

Proven experience in bioinformatics analysis of high-throughput sequencing data (e.g. NGS).
Proficiency with Python R and command-line tools in Linux/Unix environments.
Familiarity with cloud platforms (e.g. AWS Google Cloud) and HPC environments.
Strong understanding of molecular biology genetics and biostatistics.
Excellent problem-solving skills and attention to detail.
Strong written and verbal communication skills to support collaborative research.

Desired Skills:

Experience with machine learning applications in bioinformatics.
Background in single-cell RNA sequencing epigenomics or meta-genomics.
Knowledge of FAIR data principles and version control systems (e.g. Git).
Understanding of clinical bioinformatics and regulatory-compliant environments.