Executive Director, Head of Computational Discovery & Translation, Infectious Disease

The Executive Director and Head of Computational Discovery & Translation Infectious Disease will lead the creation and deployment of a next-generation AI-enabled discovery and translational platform to transform how vaccines and immune therapies are designed developed and advanced to the clinic. This role will have end-to-end ownership of a transversal discovery engine spanning neoantigen viral and bacterial antigen discoveryestablishing a rational data-driven framework that integrates multimodal datasets (genomics RNAseq single-cell proteomics and clinical data) non-canonical antigen sources iterative protein engineering and clinically anchored biomarker strategies.

The Executive Director will define and implement a unified AI and data strategy across Early Infectious Diseases building scalable platform capabilities that enable rapid high-confidence target discovery antigen and mRNA design and translational insight generation. This leader will partner closely with AstraZenecas Enterprise AI organization to embed advanced machine learning agentic approaches and data-driven decision frameworks into the core of R&Dwhile elevating AI fluency upskilling teams and driving a step-change in how science is conducted across the organization.

The candidate will set the strategy standards and decision frameworks that enable multiple programs to leverage a shared high-impact capability rather than operating within isolated assets. By integrating discovery and translational sciences into a cohesive engine the Executive Director will ensure that insights generated at the earliest stages directly inform clinical development accelerating the path to meaningful patient impact.

The Executive Director will lead a high-performing multidisciplinary platform team and deliver impact through deep cross-functional partnerships. Key interfaces will include Enterprise AI Internal Clinical Data Sciences hubs External data hubs Translational Medicine teams to ensure clinical relevance and biomarker integration and Discovery Sciences to advance protein design and validation. The role will also engage selectively with leading academic and biotech partners to access emerging technologies and reshape the internal innovation ecosystem.

Operating at the intersection of immunology data science and engineering this leader will pioneer novel out-of-the-box approaches to train the immune systemincluding next-generation strategies to target cancer and complex addition the Executive Director will inspire exceptional talent foster a culture of innovation and accountability and influence senior stakeholders to align on a bold vision for AI-enabled transformationultimately redefining how vaccines and immunotherapies are discovered developed and delivered.

Typical Accountabilities

Strategic Accountabilities

• Define and execute the AI and data strategy for Early Infectious Disease spanning discovery molecular design preclinical translation multi-dimensional analysis biomarker strategy and early clinical development.
• Establish a discovery-to-clinic AI platform vision that connects target and antigen discovery structural biology construct design functional immunology translational biomarkers and clinical decision-making.
• Partner with Early ID leadership Enterprise AI Discovery Sciences Translational Medicine Clinical Data Sciences Clinical Development Regulatory Safety CMC and Oncology to align platform priorities with portfolio needs.
• Influence senior and executive stakeholders on AI-enabled R&D strategy resource allocation external partnerships and portfolio-level decision frameworks.
• Develop build/partner/buy strategy for emerging AI immunology structural biology foundation model and agentic AI capabilities.
• Operational / Platform Accountabilities
• Build and operationalize reusable AI-enabled platform capabilities for antigen epitope neoantigen viral bacterial antibody peptide/protein mRNA and immune-therapy discovery programs.
• Establish structure-aware and sequence-aware workflows for antigen and target prioritization protein/peptide/antibody design mRNA/construct optimization developability assessment and experimental prioritization.
• Develop multimodal AI approaches integrating genomics transcriptomics single-cell proteomics structural immunological preclinical clinical and external knowledge data.
• Create closed-loop learning systems linking computational prediction assay design wet-lab and preclinical validation clinical readouts and model refinement.
• Build translational AI capabilities for immune-correlate discovery biomarker strategy patient stratification response prediction and trial-enabling decisions.
• Define model validation standards evidence packages uncertainty communication model cards reproducible workflows and decision frameworks for platform outputs.
• Ensure platform outputs are adopted by asset teams and used in governance experimental planning biomarker strategy and clinical translation.
• People / Organizational Leadership Accountabilities
• Build lead and develop a high-performing multidisciplinary team of AI scientists computational biologists ML engineers bioinformaticians and matrixed scientific collaborators.
• Establish an operating model for prioritization delivery governance stakeholder engagement and cross-functional execution across multiple programs.
• Manage direct and matrixed contributors budgets external vendors academic partnerships and biotech/technology collaborations.
• Raise AI fluency across Early ID by coaching scientific teams on AI use cases limitations interpretation validation and adoption.
• Foster a culture of scientific rigor experimental accountability platform reuse innovation and high-quality execution.
  

Essential requirements

• PhD in computational biology computer science biomedical engineering biophysics bioinformatics AI/ML structural biology or related discipline.
• MSc in Computational biochemistry or biological sciences.
• Bachelor degree in Computer science.
• 15 years of relevant industry and/or translational research experience incorporating software engineering AI/ML and computational biology in drug R&D and/or biomedical research. Proven track record building and deploying AI computational biology or translational data science platforms in drug discovery and/or clinical development.
• Demonstrated experience leading AI/data strategy across multiple stages of R&D ideally including at least in one area such as target discovery molecular design preclinical validation biomarker discovery patient stratification and clinical development.
• Strong foundation in computational biology and multimodal biological data integration including omics single-cell proteomics sequence/structure assay foundation models and clinical data.
• Experience translating computational predictions into biological experiments preclinical validation plans biomarker strategies or clinical development decisions.
• Experience with machine learning/deep learning for biological prediction multimodal modeling foundation models scientific LLMs or agentic AI workflows and software/data infrastructure.
• Proven ability to build scale and lead multidisciplinary AI/data science teams including direct and matrix leadership.
• Experience establishing operating models governance standards decision frameworks reproducible workflows and communication approaches for high-impact scientific AI.
• Experience working in a cross-functional team in industry to maximize expertise and accelerate success
• Experience developing and implementing novel computational methods to support immune-directed R&D / discovery-to-clinic AI
• Experience supporting or leading interdisciplinary discovery or development programs
• Proven experience leading and managing junior colleagues
• Proven experience developing and controlling budgets
• Excellent written and verbal communication business analysis and consultancy skills

Desirable requirements

• Comfortable working with and leading lab and computational scientists across disciplines
• Experience in immunology vaccines infectious disease oncology immunotherapy immune-mediated disease or related therapeutic areas. Proven track record of publishing relevant results and tools in peer-reviewed journals conferences and other scientific proceedings.
• Experience in life sciences and healthcare
• Experience in novel methods development and application
• Experience in a complex global organization
• Experience with structural biology protein folding protein-protein interactions developability protein engineering or sequence-to-function modeling.

Office Working Requirements

When we put unexpected teams in the same room we unleash bold thinking with the power to inspire life-changing -person working gives us the platform we need to connect work at pace and challenge perceptions. Thats why we work on average a minimum of three days per week from the office. But that doesnt mean were not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world.

The annual base pay for this position ranges from $ - Annual USD. Base pay offered may vary depending on multiple individualized factors including market location job-related knowledge skills and addition our positions offer a short-term incentive bonus opportunity; eligibility toparticipatein our equity-based long-term incentive program. Benefits offered include a qualified retirement program 401(k) plan; paid vacation and holidays; paid leaves; and health benefits including medical prescription drug dental and vision coveragein accordance withtheterms and conditions of the applicable plans.

Date Posted

Closing Date

Our mission is to build an inclusive environment where equal employment opportunities are available to all applicants and furtherance of that mission we welcome and consider applications from all qualified candidates regardless of their protected characteristics. If you have a disability or special need that requires accommodation please complete the corresponding section in the application form.