Senior Bioinformatician

Job Description

TEC Partners have a truly exciting opportunity for a Senior Bioinformatician to join a ground-breaking biotech in the Cambridge area. You will be afforded the opportunity to be part of a company that is making a tangible difference to unlocking effectivecell therapy treatments, and their Computational Biology team works on a key component of their platform. You will be working alongside a dedicated cross-disciplinary team who are striving to push the boundaries of cellular reprogramming to unlock a new generationof cell therapies.They are looking for a highly motivated senior scientist to join their expanding Bioinformatics team. Reporting to the Head of Bioinformatics, you will be joining a highly collaborative team of computational biologists with diverse skill sets who work togetherto lead decisions and analysis in discovery and characterisation of reprogrammed cell lines. This is an opportunity to join one of the best stem cell reprogramming start-ups and conduct research with a real-world impact.Senior Bioinformatician responsibilities:

• Working collaboratively with the wider computational biology team and experimental stem cell scientists.
• Leading efforts on maintenance, deployment, automation and containerisation of bioinformatic pipelines in a cloud computing environment.
• Contributing to the design and execution of our ambitious research programmes for uncovering core transcriptional programs that define human cell types.
• Performing computational analyses and reporting of results.
• Development of tools to facilitate data interpretation by laboratory scientists.

Essential requirements:

• A PhD in computational biology or a related field, 3 years of postdoctoral (or equivalent) experience in academia or industry and at least 4 years in computational biology/bioinformatics.
• Enjoy tackling research challenges through critical thinking, scientific rigour and inventiveness.
• Detail-oriented with strong organisational skills for tracking data and recording downstream analysis
• Enjoy working in a dynamic team environment and are comfortable working to tight timelines and managing workload and priorities.
• Experience in AWS cloud computing: AWS batch, AWS lambda
• Pipeline building experience: Nextflow, snakemake etc
• Familiarity with version control systems for code reproducibility.
• Strong computational fundamentals including machine learning, algorithms, and data structures.
• Proficiency in R and/or python
• Experience analysing large datasets, including next-generation sequencing data, in high-performance computing environments.
• Strong biological knowledge and interest, and familiarity with major biological data resources.
• Ability to manage and prioritise own workload

Nice to haves:

• Linux dashboard maintenance: Apache, Streamlit, RShiny
• Experience with RNA-seq (bulk and/or single cell), microarrays, ChIP-seq, ATAC-seq, and/or other genomic technologies
• Experience in data analysis of programmed human pluripotent stem cells and/or products of mammalian cell genetic engineering (CRISPR, lentiviral vectors)
• Familiarity with gene regulatory networks, mechanisms of gene expression, and developmental biology

What will you get in returnThey provide a vibrant and dynamic work environment in an exciting, fast-moving time for biology. Youll be working with cutting edge technologies and conducting pioneering work with a real-world impact.They invest in people, creating opportunities for personal development in an inclusive multi-skilled team with ambitious goals that provide opportunities to learn on the job from each other.They also offer a competitive salary, highly competitive benefits package including pension contribution scheme as well as health and life insurance.This role is with a truly revolutionary company and offers an unrivalled opportunity to be part of their journey moving forwards. If this role sounds of interest to you, please dont hesitate to get in touch directly with Jamie @ Tec Partners.

Keyskills :
BioinformaticsComputational BiologyGenomics