Bioinformatician – Discovery Full-time NEW

Bioinformatician – Discovery

Are you ready to dive into the world of transformative therapies and make a significant impact? At EsoBiotec, now part of AstraZeneca, we are setting new benchmarks for biotechnological research. Our collaboration combines AstraZeneca's global influence and scientific innovation with EsoBiotec's unique culture of creativity and breakthroughs in cell-based therapies and immunology. Here, your scientific passion will drive real-world impact as you contribute to life-changing treatments.

We are seeking a Bioinformatician to support a highly wet-lab-focused discovery research team working at the forefront of CAR-T, in vivo lentiviral delivery, and oncology. This role will help accelerate research by enabling robust analysis, interpretation, and integration of complex biological data generated across discovery and platform development activities.

The position is designed for someone who can work effectively at the interface of experimental science and computational biology. The successful candidate will partner closely with bench scientists to understand biological questions, experimental systems, and data-generation challenges, and then translate those into rigorous analytical approaches that improve insight generation, mechanistic understanding, and research decision-making.

Role Summary

As a Bioinformatician, you will work alongside researchers developing next-generation approaches in cell therapy, gene delivery, and oncology discovery. Much of the team's work is rooted in wet-lab experimentation, including cellular profiling, functional assays, perturbation studies, vector evaluation, and iterative platform optimization. Your role will be to help analyze and interpret complex biological datasets, develop reproducible workflows, and generate insights that strengthen the connection between experimental output and scientific decision-making.

This role centers on the biological and translational challenges associated with engineered cell therapies, viral delivery systems, and the interpretation of high-dimensional datasets in oncology-relevant systems. While experience with molecular profiling data is important, success in the role will come from applying bioinformatics thoughtfully in close partnership with experimental teams rather than from narrow specialization in any single assay type.

Key Responsibilities

• Partner with experimental scientists working in CAR-T, lentiviral delivery, cell engineering, and oncology discovery to understand key scientific questions, study designs, and experimental context.
• Analyze and interpret complex biological datasets generated from discovery research, including molecular profiling, perturbation, and functional assay data.
• Develop and maintain reproducible bioinformatics workflows for data processing, quality control, statistical analysis, integration, and visualization.
• Support interpretation of high-dimensional data to characterize cell states, understand perturbation effects, identify meaningful biological signals, and inform experimental priorities.
• Integrate data across assays and studies to help connect molecular readouts with phenotype, mechanism, and platform performance.
• Collaborate cross-functionally with biologists, immunologists, gene therapy scientists, data scientists, and software/informatics partners.
• Communicate analytical findings clearly with appropriate attention to assumptions, caveats, biological interpretation, and next-step recommendations.
• Help establish best practices for reproducible, rigorous, and scientifically grounded bioinformatics in discovery research.
• Apply structural biology knowledge where relevant, for example in connecting sequence, target, or construct features to mechanism and biological function.
• Monitor emerging methods in bioinformatics, computational biology, and integrative analysis, and identify opportunities to apply them meaningfully in CAR-T and in vivo delivery research.

Required Qualifications

• PhD in bioinformatics, computational biology, genomics, systems biology, biomedical engineering, biostatistics, or a related quantitative life sciences field.
• Demonstrated experience applying bioinformatics and data analysis in biological, biomedical, or R&D environments.
• Strong programming skills in R and/or Python and experience with relevant statistical and bioinformatics tools.
• Experience working with complex experimental datasets and building practical analyses that support scientific decision-making.
• Ability to work effectively with wet-lab researchers and communicate clearly across computational and experimental disciplines.
• Experience handling ambiguity and translating open-ended scientific questions into structured analytical approaches.
• Strong grounding in data quality, statistical rigor, reproducibility, and biological interpretation.

Preferred Qualifications

• Experience in one or more of the following areas: oncology, immunology, cell therapy, gene therapy, viral vector biology, lentiviral systems, or functional genomics.
• Familiarity with biological data modalities relevant to this space, including molecular profiling data, single-cell approaches, perturbation datasets, and other high-dimensional assay data.
• Experience with integrative analysis, functional genomics, single-cell data analysis, or mechanism-oriented biological interpretation.
• Understanding of the practical realities of discovery-stage wet-lab research, including assay variability, small and noisy datasets, metadata challenges, and iterative hypothesis testing.
• Some experience in structural biology or protein structure/function interpretation.
• Experience developing clear visualizations, summaries, or decision-support outputs for scientific teams.
• Familiarity with collaborative, matrixed, or fast-moving research environments.

What Success Looks Like

Success in this role means helping a wet-lab-heavy research team generate better insight from complex biological data, understand mechanisms more clearly, and use bioinformatics in ways that are scientifically credible and operationally useful. You will bring value by helping connect molecular and functional readouts to decisions around construct design, delivery strategy, cell phenotype interpretation, and experimental prioritization.

The strongest candidates will be technically capable, biologically curious, and highly collaborative. They will be comfortable operating in an environment where the data may be heterogeneous, the biology may be complex, and the most valuable contributions are often those that are rigorous, interpretable, and closely aligned to experimental reality.

Candidate Profile

The ideal candidate is a hands-on bioinformatician who enjoys working close to the science. They are excited by translational challenges in oncology, cell engineering, and in vivo gene delivery, and they know how to adapt analytical methods to real-world discovery settings rather than idealized datasets. They can listen to scientists, identify tractable opportunities, produce useful analyses, and communicate results in a way that supports better experiments and stronger decisions.

So, what is next:

Ready to make an impact? Apply now to join our mission-driven team!