Bioinformatics Scientist

15109

SciencePermanent

Posted 0 days agoApply Now

We are seeking a talented Computational Biologist or Bioinformatics Scientist to advance our target discovery platform. In this role, you'll work with cutting-edge multi-omics data to identify promising therapeutic targets and accelerate drug discovery.

You'll be responsible for processing large-scale datasets from genetics, single-cell, and proteomics studies. Your work will involve building reliable analysis pipelines, implementing SOTA methods, and developing production-ready code. The ideal candidate combines strong computational skills with a passion for translating complex biological data into actionable insights for drug development.

Key Responsibilities

Data management & preprocessing: tabular data, genetics data (plink format), GWAS sumstats, xQTL, RNA-Seq (bulk, single-cell), proteomics.
Association Analysis: WGS and WES common and rare variants associations, statistical inference, classical ML.
Post-GWAS integration & validation: genetic colocalization, mendelian randomization, transcriptomics and proteomics integration.
Pipeline development & maintenance: design, build, and maintain automated analysis pipelines for association studies, ensure code quality.

Qualifications

Education: BSc/MSc/PhD in Computational Biology, Bioinformatics, Biostatistics, Computer Science, Genetics, or related quantitative field.
Minimum of 3+ years (BSc) or 1+ years (MSc) of relevant experience (or relevant doctoral research for PhD).
Demonstrated hands-on experience analyzing large-scale omics datasets (GWAS, RNA-seq, proteomics, or other omics data).
Advances Proficiency in Python: pandas/polars/spark, matplotlib+seaborn, scipy, scikit-learn, statsmodels.
Intermediate R proficiency: ability to implement methods from research papers and modify existing code.
Proficient in a Unix/Linux command-line environment.
Practical experience with genetics and GWAS data preprocessing and analysis (plink, normalization, harmonization).
Experience with implementing post-GWAS methods (e.g. finemapping, meta-analysis, etc.).
Experience with workflow management systems (e.g., Nextflow, Snakemake, CWL) is highly desirable.
Familiarity with bulk RNA-Seq and/or scRNA-Seq principles.
Strong problem-solving skills and analytical thinking to address complex biological questions.
Ability to work both independently and collaboratively in a fast-paced research environment.
Proactive approach to learning new technologies and methodologies as the field evolves.

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Consultant

Phoebe Lole

With a background in Agriculture and Livestock Science, Phoebe began her career in the food and agriculture industry, working across FSQR, NPD, and supply chain before moving into a role supporting agricultural sustainability at a global food business. After several years in industry, she took a career break to work in the yachting sector - earning her Yachtmaster licence, skippering her own yacht, and progressing to superyachts.

Now part of the Science team at Jackson Hogg, Phoebe recruits across the UK for a wide range of science roles, ranging from lab technicians to regulatory directors, supporting clients across the life science sector. Outside of work, Phoebe enjoys hiking, trail running, and baking.

Consultant - Science

07897927166

phoebe.lole@jacksonhogg.com

Bioinformatics Scientist

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