Bioinformatics Algorithm Developer
Do you want to be part of a team developing cutting edge sequencing software solutions? Do you want to help develop software used to identify the cause of rare genetics disease and cancer?
We currently have a fantastic opportunity for a Bioinformatics Algorithm Developer to join our team.
We are seeking a self-motivated Bioinformatics Algorithm Developer who can contribute to Dragen and help develop analysis solutions for rare genetic disease and cancer. You will develop novel algorithms and analyse data from existing and emerging high-throughput DNA sequencing technologies.
The ideal candidate will enjoy problem solving and thrive on working in a fast moving environment. They will need to have strong communication skills and be comfortable working within development teams with a diverse range of technical backgrounds and across multiple locations.
You’ll join a culture fueled by innovation, collaboration and openness, and help changing lives by driving advancements in life sciences, oncology, reproductive health, agriculture and other emerging markets. Your new colleagues are all deeply passionate about what they do, knowing that our work has the power to improve lives.
Responsibilities may include:
- Define and develop algorithms and workflows under limited instruction
- Maintain and improve bioinformatics software
- Provide methods, prototypes, and code for implementation in internal tools and end-user applications
- Participate in cross-site projects and collaborations and present results to both internal and external partners
Preferred background, skills and experience:
- Bachelor’s degree or higher qualification (or equivalent) in bioinformatics, mathematics, physics, computer science or another numerate subject
- Demonstrable ability in C or C++ and a scripting language (e.g. Python, Perl, R), with an appreciation of professional software engineering tools and practices
- Demonstrable ability in the design and optimisation of algorithms (with an understanding of the key algorithms in DNA sequence analysis being highly desirable)
- Understanding of key concepts in statistics and statistical genetics
- Practical experience of open-source bioinformatics tools and libraries (e.g. htslib)
- Practical experience of Amazon Web Services or other cloud platforms