Senior Scientist - Drug Discovery (AI/ML)

This Opportunity

We are seeking a highly motivated and independent Scientist/Sr. Scientist with demonstrated experience and expertise in Computational Biology applied to Cellular Therapy, Immunology, and/or Immuno-Oncology to join our rapidly growing Cell Therapy Team.

In this role you will contribute to the advancement of innovative Cell Therapy products by developing advanced computational models using large-scale omic datasets, designing and conducting laboratory experiments, and generating and interpreting scientific data in a highly collaborative environment. The role will be based in Gaithersburg, MD, USA.

Accountabilities

• Plans, conducts, and troubleshoots discovery research experiments independently.
• Assesses and reports data with a clear understanding of its implications within the overall context of drug discovery, independently formulate conclusions, and determine future experiments
• Design, develop, and deploy AI-driven machine learning and deep learning models to extract knowledge and insights from structured and unstructured data sources relevant to the development of new therapies.
• Provides technical instruction to the team and allocates administrative work where possible
• Works collaboratively in a matrix environment
• Prepares and delivers presentations within the Cell Therapy Unit and across other functions
• Ensures own work, and work of peers, are compliant with relevant internal AstraZeneca standards and external regulations

Education and Experience

• PhD in relevant disciplines or equivalent experience (e.g. Bioinformatics, Systems Biology, Applied Mathematics, Statistics, Data Science, Computer Science)
• Minimum of 3 years of experience in Cellular Therapy, Immunology, Immuno-Oncology, Computational Biology, and/or Data Science

Essential Skills

• Proficiency in Python and/or R Prior experience in UNIX-based systems, high-performance computing (e.g. SLURM), and large-scale data management
• Expertise in omics technologies, and capable of processing large-scale biological datasets (e.g. single cell/spatial transcriptomics, in-house proprietary data sources such as in vitro or in vivo data)
• Deep understanding of AI, predictive modelling, and statistical methods applied to training of machine learning models
• Hands-on expertise in T-cell functional characterization assays such as in vitro cytotoxicity, proliferation, cytokine measurement, and multi-parameter flow cytometry
• Ability and motivation to drive projects to completion in a team environment

Desirable Skills

• Experience in drug development in an industry setting