Computational Biologist

At the Ellison Institute of Technology (EIT), we’re on a mission to translate scientific discovery into real world impact. We bring together visionary scientists, technologists, policy makers, and entrepreneurs to tackle humanity’s greatest challenges in four transformative areas:

• Health, Medical Science & Generative Biology
• Food Security & Sustainable Agriculture
• Climate Change & Managing CO₂
• Artificial Intelligence & Robotics

This is ambitious work - work that demands curiosity, courage, and a relentless drive to make a difference. At EIT, you’ll join a community built on excellence, innovation, tenacity, trust, and collaboration, where bold ideas become real-world breakthroughs. Together, we push boundaries, embrace complexity, and create solutions to scale ideas for lab to society. Explore more at www.eit.org

We’re looking for a Computational Biologist to work at the interface of microbiology and AI. The role requires being a subject matter expert within a team of AI researchers and engineers and the hands-on ability to work on projects including transforming complex biological sources into robust, high-quality data sets, building bioinformatics solutions, and designing evaluations for foundation models. 

This role requires deep expertise in microbiology and bioinformatics methods, strong scientific judgement, and the ability to critically assess and improve how biological data is used in computational systems. You will work closely with AI Scientists and Engineers to ensure models are biologically sound and capture the most important signals. 

• →Structure, curate, and transform large-scale microbiology data for use in machine learning systems  

• →Define biologically grounded tasks, representations, and evaluation frameworks aligned with real biological signal  

• →Interrogate datasets, methods, and model outputs to identify bias, leakage, and invalid assumptions  

• →Apply, adapt, and critically assess state-of-the-art bioinformatics methods in real-world settings  

• →Build robust, reproducible Python workflows and collaborate closely with research and engineering teams 

• Extensive experience in genomics and computational biology, with strong understanding of methods such as genome assembly, alignment, and variant analysis  

• Experience working with large-scale genomics datasets including data preparation and modelling 

• Proven track record of solving complex computational biology problems, translating them into computational and statistical methods and delivering working implementations. 

• High proficiency in Python for data processing and modelling 

• Background in software engineering 

• Experience with microbiology and prokaryotic biology 

• Experience with long- and short-read sequencing technologies 

• Experience with foundation models or representation learning applied to biological data