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Associate Principal AI Data Scientist – Pharmaceutical Development, Macclesfield col-narrow-left
Client: Location: Macclesfield, United Kingdom
Job Category: Other
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EU work permit required: Yes
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Job Reference: Job Views: 6
Posted: 29.06.2025
Expiry Date: 13.08.2025
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Job Description: Pharmaceutical Technology and Development (PT&D) is the organization that turns brilliant science into actual medicines that help millions of people. We work across the entire value chain, designing and delivering active ingredients, formulations and devices for new medicines and providing expert technical support to all AstraZeneca’s commercial drug substances and products to ensure we successfully supply medicines to patients.
We are looking for Associate Principal AI Data Scientists eager to utilize their expertise in these advanced technologies to revolutionise our drug development processes. In the PT&D department, you will be a key player in transforming molecules into groundbreaking medical treatments. PT&D leads the charge in developing cutting-edge synthetic routes, drug formulations and delivery technologies, ensuring our products are effective, safe, and of the highest quality.
Your role involves contributing data science expertise into cross functional global pharmaceutical development projects in support of transforming the way we deliver medicines to patients. You'll play a pivotal role in shaping our AI strategy and driving the co-development of sophisticated HITL multi-agent systems.
We are hiring two candidates for this position and the roles will be based at our dynamic sites in Gothenburg (Sweden) or Macclesfield (UK).
Accountabilities:
Drive innovation in agentic AI, multi-agent systems, and digital twins, exploring new methodologies and applications.
Design, implement, and optimize algorithms for autonomous decision-making, coordination, and policy learning among agents and digital twins using techniques like Markov Decision Processes (MDPs), Partially Observable MDPs (POMDPs), and multi-agent reinforcement learning (MARL).
Evaluate agent performance in the context of decision making, collaboration, competition, uncertainty.
Collaborate with cross-functional teams ensuring knowledge transfer to IT engineering teams for IT solution builds and deployment.
Keep pace with industry advancements by reviewing academic papers and attending conferences. Publish findings in peer-reviewed journals and represent the company at scientific forums.
Communicate technical concepts and results to technical and non-technical audiences.
Essential skills/experience:
Advanced degree in computer science, data science, artificial intelligence, machine learning or related fields.
Excellent coding skills in languages such as Python, R.
Hands-on industrial experience designing multi-agent patterns, digital twins and experience with agentic AI design patterns, reinforcement learning.
Extensive industrial experience with AI and ML frameworks like TensorFlow, PyTorch,
Hands-on experience with GenAI orchestration frameworks such as LangGraph, CrewAI.
Hands-on experience with reinforcement learning libraries such as OpenAI Gym, Ray RLlib, or Stable Baselines.
Hands-on industrial experience with applied machine learning domains such as deep learning, NLP, GenAI.
Contributions to open-source projects. If you meet these criteria, please highlight merged GitHub PRs in your application.
Strong publication record in the field of AI.
Experience designing multi-agent systems in the pharmaceutical sector.
Experience delivering machine learning projects with applications in pharmaceutical development, chemical engineering or chemistry.
Experience with one or more of the following applied machine learning domains such as transfer learning, federated learning, few/zero shot learning, meta learning, explainable AI.
When we put unexpected teams in the same room, we unleash bold thinking with the power to inspire life-changing medicines. In-person working gives us the platform we need to connect, work at pace and challenge perceptions. That's why we work, on average, a minimum of three days per week from the office. But that doesn't mean we're not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world.
AstraZeneca is a place where change is embraced, and new solutions are trialed with patients and business in mind. Here, technology is a key lever for delivering medicines quickly, affordably, and sustainably. Our diverse workforce is united by curiosity, sharing learnings to scale fast. Be part of a digitally-enabled environment that impacts all parts of the business—from robotic process automation to machine learning for quality batches—while contributing to society and the planet.
Ready to make a difference? Apply now to join our team! Welcome with your application no later than July 1st 2025 .
Competitive salary and benefits package on offer.
Date Posted
25-juni-2025 Pharmaceutical Technology and Development (PT&D) is the organization that turns brilliant science into actual medicines that help millions of people. We work across the entire value chain, designing and delivering active ingredients, formulations and devices for new medicines and providing expert technical support to all AstraZeneca’s commercial drug substances and products to ensure we successfully supply medicines to patients.
We are looking for Associate Principal AI Data Scientists eager to utilize their expertise in these advanced technologies to revolutionise our drug development processes. In the PT&D department, you will be a key player in transforming molecules into groundbreaking medical treatments. PT&D leads the charge in developing cutting-edge synthetic routes, drug formulations and delivery technologies, ensuring our products are effective, safe, and of the highest quality.
Your role involves contributing data science expertise into cross functional global pharmaceutical development projects in support of transforming the way we deliver medicines to patients. You'll play a pivotal role in shaping our AI strategy and driving the co-development of sophisticated HITL multi-agent systems.
We are hiring two candidates for this position and the roles will be based at our dynamic sites in Gothenburg (Sweden) or Macclesfield (UK).
Accountabilities:
Drive innovation in agentic AI, multi-agent systems, and digital twins, exploring new methodologies and applications.
Design, implement, and optimize algorithms for autonomous decision-making, coordination, and policy learning among agents and digital twins using techniques like Markov Decision Processes (MDPs), Partially Observable MDPs (POMDPs), and multi-agent reinforcement learning (MARL).
Evaluate agent performance in the context of decision making, collaboration, competition, uncertainty.
Collaborate with cross-functional teams ensuring knowledge transfer to IT engineering teams for IT solution builds and deployment.
Keep pace with industry advancements by reviewing academic papers and attending conferences. Publish findings in peer-reviewed journals and represent the company at scientific forums.
Communicate technical concepts and results to technical and non-technical audiences.
Essential skills/experience:
Advanced degree in computer science, data science, artificial intelligence, machine learning or related fields.
Excellent coding skills in languages such as Python, R.
Hands-on industrial experience designing multi-agent patterns, digital twins and experience with agentic AI design patterns, reinforcement learning.
Extensive industrial experience with AI and ML frameworks like TensorFlow, PyTorch,
Hands-on experience with GenAI orchestration frameworks such as LangGraph, CrewAI.
Hands-on experience with reinforcement learning libraries such as OpenAI Gym, Ray RLlib, or Stable Baselines.
Hands-on industrial experience with applied machine learning domains such as deep learning, NLP, GenAI.
Desirable skills /experience :
Contributions to open-source projects. If you meet these criteria, please highlight merged GitHub PRs in your application.
Strong publication record in the field of AI.
Experience designing multi-agent systems in the pharmaceutical sector.
Experience delivering machine learning projects with applications in pharmaceutical development, chemical engineering or chemistry.
Experience with one or more of the following applied machine learning domains such as transfer learning, federated learning, few/zero shot learning, meta learning, explainable AI.
When we put unexpected teams in the same room, we unleash bold thinking with the power to inspire life-changing medicines. In-person working gives us the platform we need to connect, work at pace and challenge perceptions. That's why we work, on average, a minimum of three days per week from the office. But that doesn't mean we're not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world.
AstraZeneca is a place where change is embraced, and new solutions are trialed with patients and business in mind. Here, technology is a key lever for delivering medicines quickly, affordably, and sustainably. Our diverse workforce is united by curiosity, sharing learnings to scale fast. Be part of a digitally-enabled environment that impacts all parts of the business—from robotic process automation to machine learning for quality batches—while contributing to society and the planet.
Ready to make a difference? Apply now to join our team! Welcome with your application no later than July 1st 2025 .
Competitive salary and benefits package on offer.
Opening date: June 25th, 2025
Closing date: July 1st, 2025
Date Posted
25-juni-2025 Closing Date
01-juli-2025Our 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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