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Associate Principal Scientist, Machine Learning

AstraZeneca UK

Location: Cambridgeshire

Job Type: Full time

Posted


Do you have expertise in, and passion for, Senior Machine Learning Scientist, Biologics Optimization? Would you like to apply your expertise to impact on programs in Cancer, Inflammation, Cardiovascular, Metabolic Disease and Infectious Disease in a company that follows the science and turns ideas into life changing medicines? AstraZeneca might be the one for you!

AstraZeneca has an opening for a Senior Machine Learning Scientist, Biologics Optimization group within the Biologics Engineering Department to support pre-clinical research of innovative therapeutic products. An expertise in core and innovative molecular biology techniques is needed. This role would be based in our Gaithersburg site.

Business Area:

The Biologics Engineering team is responsible for the discovery and optimisation of next generation biological drug candidates for all key therapy areas across AstraZeneca, and for developing in-house biologics discovery platforms and novel drug modalities to address unmet medical needs.

Central to this effort is the development of end-to-end data management and analysis capabilities to deliver novel biologics drugs. You will be part of an interdisciplinary Bioinformatics team, working at the cutting edge of research and development to create an active learning system for biologics engineering, in which model predictions guide lab experiments, lab automation generates high-throughput data for model training, and predictive models are updated as new data are generated. As part of this effort, you will collaborate closely with experts in data management, software engineering, lab automation, computational modelling, and machine learning, with access to biologics R&D data across AstraZeneca and the potential to generate new data to inform predictive models.

What you’ll do

This role provides the opportunity for a dedicated and motivated machine learning scientist to develop end-to-end machine learning capabilities that will significantly impact the delivery of the novel biologics drugs of the future.

  • Work collaboratively with data and drug discovery scientists to develop machine learning methods that inform subsequent experiments for optimizing biologics design.

  • See opportunities across biologics engineering where machine learning can inform subsequent experiments. Make recommendations for additional data and metadata to be collected.

  • Work collaboratively with machine learning guides in antibody design to incorporate state-of-the art methods within an end-to-end active learning system.

  • Grow your expertise in biologics engineering by learning from leading scientists in the field. Use your combined expertise in biologics engineering and machine learning to identify new opportunities to substantially improve biologics design.

  • Build and maintain high level of experience with Biologics Engineering team's informatics environment and train bench scientists in data management and analyses processes, including verification of data quality

  • Engage in strategic external collaborations, with the opportunity to publish research in leading journals and conferences.

  • Support testing and verification of data analysis tools and pipelines in collaboration with AstraZeneca partners.

  • Demonstrate effective communication to translate complex concepts to non-experts in internal and external scientific meetings.

Essential for the role

  • PhD or equivalent experience in a relevant computational field.

  • Experience working with machine learning methods and their application to molecular biology.

  • Experience with Python for analysis of experimental data.

  • Strong communication skills and excellent attention to detail, capable of developing good working relationships with diverse individuals.

  • Experience working within a team environment.

  • Acts with integrity and does the right thing.

Desirable for the role

  • Experience with active learning and Bayesian optimization.

  • Awareness of data requirements for using machine learning to model biological data.

  • Experience incorporating domain knowledge from biology into machine learning methods.

  • Familiarity with antibody discovery.

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 daring - finding those moments and recognizing their potential. Join us on our journey of building a new kind of organization to reset expectations of what a bio-pharmaceutical company can be. This means we’re opening new ways to work, pioneering innovative methods and bringing unexpected teams together. Interested? Come and join our journey.

So, what’s next?

  • Are you already inspiring yourself joining our team? Are you ready to bring new insights and fresh thinking to the table? Good, because we can’t wait to hear from you!

Competitive salary & benefits

Close date: 02/12/2022

Where can I find out more?

Our Social Media, Follow AstraZeneca on LinkedIn https://www.linkedin.com/company/1603/

Follow AstraZeneca on Facebook https://www.facebook.com/astrazenecacareers/

Follow AstraZeneca on Instagram https://www.instagram.com/astrazeneca_careers/?hl=en

Date Posted

25-Nov-2022

Closing Date

01-Dec-2022

AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.