Scientist

The Mission

Drug discovery has a translation problem: more than 95% of drugs that succeed in animal models fail in humans. We're building the alternative: human-first drug discovery, powered by organoids and AI, running on real human biology from the very first experiment.

Our platform is 87% concordant with clinical patient data - a vast improvement over the 3% translational success rate of animals. We’ve demonstrated the ability to model immunotoxicology, immunogen stimulation, and two autoimmune diseases with more on the way. Numerous pharma partners including 3 Fortune 500 companies are already using the platform. We've raised ~$30M from AIX Ventures, Marc Benioff, Jeff Dean, and Y Combinator. With the FDA Modernization Act 3.0 and the FDA's March 2026 validation framework, the regulatory tailwinds only continue to get stronger.

The opportunity ahead of the company is generational: build the first scaled engine for generating real human biological data, and use it to fundamentally change how medicines are discovered.

The Role

Note to candidates: the list below describes a strong profile, not a set of hard requirements. If you do not match every point but believe you are a strong candidate, please apply.

Parallel Bio is redefining human-first drug discovery. Our platform runs high-throughput immune organoid experiments to accelerate the development of new therapeutics. What makes that valuable is not the engineering of the system itself. It is recognising what these models show that simpler systems cannot, and designing experiments whose outputs connect to decisions in drug development. The most common failure in platform biology is invisible: technically sound experiments that never ask a question only this system could answer.

We are looking for a scientist with a broad immunology background who understands how immune function emerges at the tissue level, who has enough proximity to drug development to recognise translatable evidence, and who designs experiments that produce it. Disease-specific expertise is welcome but not expected. Breadth matters more, since the programme will move across indications as it develops.

The high-level goals for this role are threefold:

1. Build and validate immune organoid models, from tissue handling and cell isolation through to functional immunological readouts.

2. Advance disease modelling on the platform and improve immune system modelling, assay design and integration with other biological systems.

3. Make experimental work reproducible and well enough documented to transfer, and partner with the automation and computational teams as the platform scales.