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Wien, Österreich
Onsite
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.
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:
Build and validate immune organoid models, from tissue handling and cell isolation through to functional immunological readouts.
Advance disease modelling on the platform and improve immune system modelling, assay design and integration with other biological systems.
Make experimental work reproducible and well enough documented to transfer, and partner with the automation and computational teams as the platform scales.
This is a hands-on research role with a high degree of independence. The project is one to own end to end: designing and executing the experiments, making the scientific and technical calls that move the work forward, and running several workstreams in parallel. The work is at the bench, running the experiments as well as designing them, with the hands-on element expected to stay constant as the team grows. Note that maintaining cell cultures and experimental continuity requires some weekend work on a rotating basis.
Design, execute and interpret immune organoid experiments in tissue culture, working with primary human cells and stem cell-derived models.
Establish, optimize and troubleshoot assays for immune activation, cell phenotyping and functional response.
Connect what is observed at the bench to what would matter for a drug development decision, and design experiments accordingly.
Take on the open-ended work, where the approach is unsettled and the answer comes through trial and error rather than a defined protocol.
Set the direction of the project, decide on experimental priorities and adjust the plan as the data come in.
Run multiple projects concurrently and manage timelines against defined milestones.
Work with the computational and automation teams so that biological interpretation shapes what the platform investigates next.
Use the automation available in the lab, and give input on what would be useful next.
Write and implement SOPs that hold up to transfer between sites.
Produce clear experimental documentation and contribute to reports and presentations.
Share knowledge with peers and junior researchers, present findings in internal meetings and challenge conclusions, including ours.
Mentor junior scientists as the team grows.
Flag when the data does not support the conclusion being drawn, and report ambiguous results with the same care as clean ones.
PhD in immunology, cell biology or a closely related life sciences discipline, with 5+ years of experience in biotech, pharma or a research environment with exposure to translational or drug development contexts.
Broad immunological expertise across innate and adaptive immunity, with strong practical command of immune cell characterisation.
Experience with secondary lymphoid organ biology. This can come from several backgrounds, including ex vivo tissue studies, spatial transcriptomics or proteomics of immune tissue, and mucosal immunology.
Strong background in primary cell and tissue culture, including 3D or organoid culture.
Familiarity with immunological characterisation methods. Flow cytometry panel design and analysis, multiplex immunoassays and imaging-based readouts are core to the role.
Experience with iPSC culture or differentiation is useful but not required.
Comfort with quantitative analysis, including scripting in Python, R or equivalent, data visualisation and working directly with complex datasets. Computational biology as a specialism is not required.
Experience developing disease-relevant immune models, whether autoimmune, inflammatory or immuno-oncology, is valued.
Strong record of documenting experiments and communicating results.
Track record of driving a project independently, from experimental design through to interpretation and decision-making, with limited day-to-day supervision.
Comfortable holding several projects in parallel and setting priorities between them independently.
Able to hold competing biological explanations without settling on one prematurely, and to distinguish what data is consistent with from what it demonstrates.
Able to troubleshoot complex experimental systems and decide when to change approach.
Excellent collaborator with a history of working across disciplines and across sites.
Interest in contributing to a growing, international team.
Vienna, Austria
Your compensation package will include a minimum base salary of €60,000 annually, based on full-time engagement. The final amount will be determined by experience and qualifications. This is a full-time position with no overtime compensation; the agreed salary covers all working hours. Flexible work arrangements may be possible to support work-life balance.
Parallel Bio is an equal opportunity employer committed to fostering an inclusive and respectful workplace. We encourage applications from individuals of all backgrounds, regardless of age, gender, ethnicity, religion, disability, or sexual orientation.
