Bioinformatics Scientist

Job Title: Bioinformatics Scientist - Based in Cambridge, UK

The Company
PredictImmune was created in early 2017 as a spin-out from the Department of Medicine, University of Cambridge UK.

It is a new generation molecular diagnostics company offering a unique approach for the prognosis of immune-mediated diseases such as Inflammatory Bowel Disease, Lupus, Multiple Sclerosis etc. with a mission of “enabling better treatment and outcomes for patients with chronic immune mediated diseases”

PredictImmune has developed and is launching its first prognostic test that is simple, robust and based on RT-PCR with a unique software algorithm for identification of patients with a high or low risk of disease progression in the next 12-18 months, using whole blood samples for use in routine in clinical laboratories. We are the first company to offer predictive tests in Inflammatory Bowel Disease and aim to develop test for other immune-mediated diseases which will facilitate personalised treatment and thereby improve patient outcomes and health economics.

PredictImmune will provide its proprietary technology as both a laboratory service and as a kit depending on the needs of global markets. Currently PredictImmune has built a strong internal development and commercialisation team to creativity develop, validate and bring to market these unique and proprietary Prognostic tests via strategic partnering model throughout the global, while carrying out partnerships with a number of key Pharma companies in the Immunology sector on patient stratification and clinical studies. This will involve appointing an exclusive central lab partner in each region to perform and sell the test, while we support and influence regulators in major regions.

PredictImmune has already started this commercial process and is expecting to be making product revenues in 2019 and become profitable in 2021.

The Position
We are seeking a highly talented and creative Bioinformatics Scientist to join our fast-growing team. You will work in a team environment to visualise & analyse gene expression data sets, write scripts for multi-dimensional data analysis and support computational pipeline design and development activities. You will be expected to select and apply statistical techniques to analyse and integrate large datasets and work in close collaboration with scientists and clinicians to interpret your analysis results. You must be technically flexible and comfortable with multi-tasking both analytical and programming assignments.

This position requires:
- PhD in bioinformatics (or equivalent) or MSc in bioinformatics (or equivalent) plus 3+ years relevant experience
- Experience of analysing complex gene expression data sets
- Practical understanding of bio-statistical methods
- Demonstrated programming fluency (e.g. R, python, perl)
- Sound understanding of key computer science concepts (e.g. algorithm implementation) and practices (e.g. version control, agile development and code review)

The following skills/experiences are desirable:
– Bioinformatics/computational biology
– Gene expression data analysis (prior experience working on classification/machine learning problems a bonus)
– Statistical/bio-statistical method application
– Programming/scripting skills

In addition to the above, you are expected to have:
– Bioinformatics/Computational biology qualification
– Exceptional communication skills
– Demonstrable excellence in problem solving within fixed timelines
– Flexibility and the ability to effectively manage multiple concurrent projects

What you'll get in return
This is an excellent opportunity to help successfully build PredictImmune’s pipeline of products from concept to completion and in return we offer a competitive salary package + benefits including Life Assurance, Healthcare, Pension and stock options.

Application Instructions: 

If you feel you have got what it takes to join a vibrant and dynamic company, then we would love to hear from you. Please send your CV and covering letter to:

Application Closing Date: 
31 January