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Employer AstraZeneca Location Cambridge, Cambridgeshire, United Kingdom Salary Competitive Closing date 5 Jul 2025

View more categories View less categories Discipline Maths & IT ,AI/Cybernetics Position Type Contract Hours Full Time Result Type Jobs

Job Title: AI, Machine Learning and Cheminformatics role - (1 year Fixed Term contract )

Location: Cambridge, UK

Salary: Competitive + Excellent Employee Benefits!

Applications Deadline: July 14

Do you have expertise in, and passion for machine learning and cheminformatics? Would you like to apply your expertise to impact the design of drug candidates in a company that follows the science and turns ideas into life changing medicines? Then AstraZeneca might be the one for you!

ABOUT ASTRAZENECA

AstraZeneca is a global, science-led, patient-focused biopharmaceutical company that focuses on the discovery, development and commercialisation of prescription medicines for some of the world's most serious diseases. But we're more than one of the world's leading pharmaceutical companies.

Here you'll have the chance to create a meaningful difference to patients' lives. With science at its heart, this is the place where breakthroughs born in the lab become transformative medicines - for the world's most complex diseases. Answer unmet medical needs by pioneering the next wave of science, focusing on outcomes and crafting the patient ecosystem. With our ground-breaking pipeline, the outlook is bright. Be proud to be part of a place that has achieved so much, yet is still moving forward. There's no better time to join our global, growing enterprise as we lead the way for healthcare and society.

SITE DESCRIPTION

Welcome to Cambridge, home to many of our AstraZeneca sites. The site for this position is The Discovery Centre on the Cambridge Bioscience Campus, close to Central Cambridge and is located within walking distance from the Train station. You will have access to an onsite gym, restaurant facilities you will benefit from Lunch & Learn development activities, all within a bright and spacious environment while utilising the most advanced technology.

BUSINESS AREA

Be part of fulfilling our ambition to be world leaders in Oncology. We are already the fastest growing team within AstraZeneca and across the industry, and there are countless new indications and targets in our game-changing pipeline. We deliver this value through launch excellence, commercial efficiency and improving the lifecycle. By leveraging our commercialised portfolio we are confident we can change the practice of medicine and redefine cancer treatment.

What You'll Do

Artificial Intelligence and Machine Learning have the potential for profound impact in drug discovery. We are looking for an enthusiastic scientist to join our computational chemistry team, to apply these technologies to chemistry design challenges within the Oncology therapeutic area.

As a key part of this initiative you will work with cutting-edge AI approaches for molecular de novo design, build machine learning models and use these models - together with the project teams - to impact drug design quality and timelines. You will work with the development team to further develop new approaches for molecular de novo design.

The role is a fixed 1-year term and is suitable for an early-career scientist with experience of cheminformatics and machine learning, looking to expand their expertise within a pharmaceutical drug discovery setting. Our team is based in Cambridge, UK, but we collaborate regularly with colleagues at our other 'hub' locations in Gothenburg, Sweden and Boston, USA.

You will:

• Impact multiple discovery projects simultaneously by efficiently and pro-actively applying a wide variety of machine learning methods and building models for molecular de novo design

• Develop machine learning methods for the prediction of affinity, selectivity and ADME properties, including curating appropriate datasets.

• Drive scientific progress in applying machine learning in drug discovery

• Learn about, and be able to apply a range of computer-aided drug design tools and methodologies

Essential for the role

• Ph.D. degree in computational chemistry or cheminformatics; or B.Sc./M.Sc with equivalent experience

• Expertise in applying machine learning (e.g. Deep Learning, SVM, Random Forest)

• Broad knowledge of cheminformatics concepts

• Experience with programming (e.g. Python, C++, Java)

• Excellent collaboration and networking skills

• Innovative problem-solver

• Strong oral and written communication skills, team-working and time-management skills

Why AstraZeneca?

At AstraZeneca we're dedicated to being a Great Place to Work. Where you are empowered to push the boundaries of science and unleash your entrepreneurial spirit. There's no better place to make a difference to medicine, patients and society. An inclusive culture that champions diversity and collaboration, and always committed to lifelong learning, growth and development. We're on an exciting journey to pioneer the future of healthcare.

So, what's next?

• Are you already imagining yourself joining our team? Good, because we can't wait to hear from you.

• Are you ready to bring new ideas and fresh thinking to the table? Brilliant! We have one seat available and we hope it's yours.

• We encourage you to apply online before July 14

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
23-Jun-2025

Closing Date
13-Jul-2025

Our mission is to build an inclusive and equitable environment. We want people to feel they belong at AstraZeneca and Alexion, starting with our recruitment process. We welcome and consider applications from all qualified candidates, regardless of characteristics. We offer reasonable adjustments/accommodations to help all candidates to perform at their best. If you have a need for any adjustments/accommodations, please complete the section in the application form.

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