25.03.25 Machine Learning Scientists/Engineers, Cambridge, UK
25.03.25 Machine Learning Scientists/Engineers, Cambridge, UK

25.03.25 Machine Learning Scientists/Engineers, Cambridge, UK

Full-Time 36000 - 60000 £ / year (est.) No home office possible
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At a Glance

  • Tasks: Drive innovative machine learning methods for drug discovery and optimisation.
  • Company: Astex Pharmaceuticals, a leader in drug discovery and development.
  • Benefits: Competitive salary, hybrid working options, and excellent career development opportunities.
  • Why this job: Make a real impact in healthcare by advancing AI in drug discovery.
  • Qualifications: PhD or equivalent experience in a technical field and strong ML background.
  • Other info: Collaborative environment with access to extensive structural datasets.

The predicted salary is between 36000 - 60000 £ per year.

Astex Pharmaceuticals is a world leader in innovative drug discovery and development. The company has successfully applied its proprietary Fragment-Based Drug Discovery platform to generate multiple new drug candidates that are progressing in clinical development. Successful collaborations have led to three launched oncology drugs (Kisqali partnered with Novartis, Balversa partnered with Janssen and Truqap partnered with AstraZeneca). Astex continues to grow and focuses on Neurological Disorders and Oncology.

We are seeking multiple Permanent and 3-Year Fixed-Term Contract opportunities to drive the development of innovative machine learning methods for structure-based drug discovery. In this role, you will contribute to advancing computational tools that impact the design and optimisation of novel therapeutics. You will work with one of the largest and most comprehensive internal structural datasets in the industry – our extensive collection of proprietary protein-ligand complexes developing and applying cutting-edge AI techniques, including co-folding, to unlock new insights and capabilities in molecular modelling and virtual screening. This is a collaborative opportunity to push the boundaries of ML within drug discovery, working alongside multidisciplinary teams across computational chemistry, structural biology, and data science.

Responsibilities

  • Design and implement ML models for structure-based design, including protein-ligand interaction modelling and co-folding applications.
  • Develop and extend AI approaches that integrate structural and chemical data to improve virtual screening and molecular design workflows.
  • Leverage Astex’s world-leading proprietary structural datasets to train, benchmark, and validate new algorithms.
  • Collaborate closely with cross-functional teams to ensure effective translation of research into production-ready solutions.

Profile and Skills

  • PhD or equivalent experience in a technical discipline (e.g., computer science, chemistry, physics, engineering).
  • Strong background in machine learning, including experience with deep learning and/or generative models.
  • Proficiency with modern ML frameworks (e.g., PyTorch, TensorFlow, or JAX).
  • Strong coding skills (e.g., Python, C++) and a collaborative mindset.
  • Familiarity with protein structure modelling, co-folding, or related structure-based methods, along with a working knowledge of organic chemistry would be desirable.

Why Astex

We offer excellent training and career development opportunities as well as a highly competitive salary and benefits package including hybrid working options to promote a flexible and inclusive work environment. The company is situated 2.5 miles from Cambridge City centre. Cambridge Science Park has onsite sports facilities and excellent transport links to London. At Astex we embrace diversity and equality of opportunity. We are committed to building an inclusive and diverse company representing all backgrounds, harnessing industry-leading scientific innovation and behaviours.

Application Information

To apply, please visit our recruitment website and submit your application before the closing date: 30 April 2025.

25.03.25 Machine Learning Scientists/Engineers, Cambridge, UK employer: The Computational Chemistry List

Astex Pharmaceuticals is an exceptional employer, offering a dynamic work environment in the heart of Cambridge, where innovation meets collaboration. With a strong focus on employee development, competitive salaries, and flexible hybrid working options, Astex fosters a culture of inclusivity and diversity, empowering its team to push the boundaries of machine learning in drug discovery. The company's proximity to Cambridge Science Park provides access to state-of-the-art facilities and excellent transport links, making it an ideal location for professionals seeking meaningful and rewarding careers in the pharmaceutical industry.
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Contact Detail:

The Computational Chemistry List Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land 25.03.25 Machine Learning Scientists/Engineers, Cambridge, UK

✨Tip Number 1

Network like a pro! Reach out to people in the industry, attend meetups, and connect with professionals on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.

✨Tip Number 2

Show off your skills! Create a portfolio showcasing your machine learning projects, especially those related to drug discovery. This will give potential employers a taste of what you can bring to the table.

✨Tip Number 3

Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice common ML interview questions and be ready to discuss your past projects in detail.

✨Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in joining Astex and contributing to our innovative work.

We think you need these skills to ace 25.03.25 Machine Learning Scientists/Engineers, Cambridge, UK

Machine Learning
Deep Learning
Generative Models
Python
C++
PyTorch
TensorFlow
JAX
Protein Structure Modelling
Co-Folding
Virtual Screening
Molecular Design
Data Science
Collaborative Mindset
Organic Chemistry

Some tips for your application 🫡

Tailor Your CV: Make sure your CV is tailored to the role of Machine Learning Scientist/Engineer. Highlight relevant experience, especially in machine learning and drug discovery, to show us you’re a perfect fit for our team.

Craft a Compelling Cover Letter: Your cover letter should tell us why you're passionate about this role and how your skills align with our mission at Astex. Be genuine and let your personality shine through!

Showcase Your Projects: If you've worked on any projects related to machine learning or drug discovery, make sure to mention them! We love seeing practical applications of your skills, so don’t hold back.

Apply Through Our Website: Remember to apply through our recruitment website! It’s the best way for us to receive your application and ensures you’re considered for the role. Don’t miss out!

How to prepare for a job interview at The Computational Chemistry List

✨Know Your Stuff

Make sure you brush up on your machine learning concepts, especially those related to drug discovery. Familiarise yourself with the latest AI techniques and frameworks like PyTorch or TensorFlow, as these will likely come up in conversation.

✨Show Your Collaborative Spirit

Astex values teamwork, so be ready to discuss your experience working in multidisciplinary teams. Share examples of how you've collaborated with others in the past, particularly in projects involving computational chemistry or structural biology.

✨Prepare for Technical Questions

Expect some technical questions that test your coding skills and understanding of protein-ligand interactions. Practise coding problems in Python or C++ and be prepared to explain your thought process clearly.

✨Ask Insightful Questions

At the end of the interview, have a few thoughtful questions ready about Astex's projects or their approach to machine learning in drug discovery. This shows your genuine interest in the role and helps you assess if it's the right fit for you.

25.03.25 Machine Learning Scientists/Engineers, Cambridge, UK
The Computational Chemistry List

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