Associate Director, AI Research Lead for Omics, Oncology Data Science

Key Skills

Aartificial intelligence, Data science techniques, Data Wrangling, Deep Learning, Effective communication skills, Leadership, Machine learning techniques, Molecular biology, Python Programming, R Programming

Job Description

Are you passionate about driving insights with data? Do you often ask yourself, if I just had these data, I could...? Do you sometimes imagine what our lives will look like three years from now in these times of the convergence of the AI and the bio revolutions? If the answer is “YES” to all the questions above and you have an interest for applying Machine Learning/AI in the computational biology space – then we have an exciting opportunity for you.

AstraZeneca is a company that always follows the science and turns ideas into life changing medicines. Oncology Data Science plays a unique role in driving drug discovery and translating basic science to clinical practice. We strive to improve the utilization of data to patients’ benefit by leading the adoption and development of computational/data driven approaches to all aspects of the drug discovery process.

Our Gaithersburg, Maryland facility creates life-changing medicines for people around the world. This campus employs more than 3,500 experts in our field and is only a short drive from Washington, DC. This modern and vibrant scientific campus is the home of R&D and Oncology in the US. Here, we play host to some of the most cutting-edge technology and lab spaces, all designed to inspire collaboration and cross-functional science. We believe employees benefit from being challenged and inspired at work. We are dedicated to creating a culture of inclusion and collaboration.

The Gaithersburg site offers a variety of amenities to help boost productivity and help keep our employees happy and healthy. This includes a fitness center, employee healthcare clinic, electric vehicle charging stations, dry cleaning, full-service cafeteria and copy center. This is where you’ll find newly-designed, activity-based work spaces

The Data Science and AI research team in oncology is composed of a diverse group of data scientists, algorithm developers and applied mathematicians working together with computational biologists, bioinformaticians, software engineers, biologists and oncologists to deliver the next drug, next biomarker and next insights to the benefit of cancer patients. Our group is pioneering new Data Science and AI methods and practices to drive drug discovery.

As AI is playing a bigger role in our lives, data is becoming more abundant, more diverse and more complex. ML/AI methods and techniques are expending - we need more experts to drive our ground-breaking research to find the right drug, to the right patient at the right time.

We are looking for truly skillful people with hands-on ability and clear thinking. People who are ambitious that are not afraid to try out stuff and fail, motivated to make an impact and pioneer new tech and science; a scientist to lead the research and development of new AI methods and practices to drive insights from high dimensional omics data. This is a rare opportunity to lead and develop new approaches combining computational biology and advanced AI, utilizing a breadth of omics data from biobanks and clinical studies to data generated using ex-vivo platforms. The successful execution of this role will directly impact our patients through discovery of biomarkers, informing optimal drug combination and patient selection strategies, discovery of novel oncology targets and furthering our knowledge of cancer biology and evolution. To do this you will:

• Design and develop new state-of-the-art methods and algorithms for integration of preclinical, ex-vivo and clinical multi-’omic data. These methods include but are not limited to using dimensionality reduction, representation learning and other techniques, both from classical ML and DL best practices.
• Combine expertise in AI methodology development and computational biology knowledge to invent new algorithms that will advance our capabilities to solve problems in high dimensional biological/molecular data.
• Partner closely with scientists across translational medicine, bioscience, software engineering and bioinformatics to shape together the AI multi-omics strategy to drive biological insights.
• Communicate results, methods and practices to teams across the organization.
• Publish results in scientific journals and present in scientific conferences.
• Work in a dynamic and multidisciplinary research environment, adapt quickly to new technologies and methods.

Minimum Qualifications:

• A PhD in a multidisciplinary subject area at the intersection of data science and biology (e.g. computational biology, bioinformatics, quantitative biology, etc.) OR a combination of quantitative and biological sciences (e.g. Bachelor in computer science and a PhD in Biology or an MD) OR a PhD in quantitative sciences (e.g. computer science, math, stats, ML/AI, Physics, computational biology, engineering) with 5 years demonstrated experience in computational biology
• Demonstrated strong technical skills including: applying and developing methods and algorithms in ML/AI, data sciences best practices, problem solving and analytical thinking.
• At least 3 years of experience in biopharma/biotech/hitech industry or academia developing methods in data science and AI.
• At least 2 years of experience in working with omics related data (e.g. genomics, scRNAseq).
• Excellent Data Wrangling skills.
• Excellent communication skills.
• R and/or Python programming expertise in a Unix environment making use of high-performance computing environments.

Desirable Qualifications:

• Publications in the field of DS & AI and/or computational biology.
• Excellent academic record.

Why AstraZeneca

At AstraZeneca when we see an opportunity for change, we seize it and make it happen, because any opportunity no matter how small, can be the start of something big. Delivering life-changing medicines is about being entrepreneurial - finding those moments and recognising their potential. Join us on our journey of building a new kind of organisation to reset expectations of what a bio-pharmaceutical company can be. This means we’re opening new ways to work, pioneering cutting edge methods and bringing unexpected teams together. Interested? Come and join our journey.