Computational Chemist & AI Engineer

Skills Alliance
Leeds
1 month ago
Applications closed

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AI Scientist – Computational Chemistry & Machine Learning

A technology-driven company at the forefront of scientific innovation is seeking anAI Scientistwith expertise incomputational chemistryandapplied machine learningto help develop transformative tools for drug discovery and partner success.

Key Responsibilities

  • Build and maintain strong relationships with external partners, delivering high-impact, transformational AI projects.
  • Collaborate with multidisciplinary teams—including data scientists, software engineers, and product teams—to integrate emerging technologies into real-world solutions.
  • Design and implementcutting-edge AI algorithms, ensuring their integration intorobust, production-grade platformsthat enhance research efficiency.
  • Translate scientific and business goals intoscalable and maintainable softwaresolutions.
  • Own thefull development lifecycle, from requirements gathering through to planning, coding, testing, and deployment.
  • Stay current onadvancements in computational science and AI, applying relevant innovations to project work.

Core Qualifications

  • MSc or PhD inComputational Chemistry,Cheminformatics,Quantum Mechanics, orAI for scientific discovery.
  • Demonstrated impact in previousscientific or technical projects, ideally within the life sciences or drug discovery space.
  • Advanced programming skills, especially inPython; experience in other languages (e.g.,C/C++,Java) is a plus.
  • Strong communicator, able toclearly articulate scientific ideasto diverse technical and non-technical audiences.
  • Collaborative, growth-oriented mindset with a passion forrapidly translating novel research into real-world applications.

Preferred Experience

Expertise in one or more of the following areas:

  • Artificial Intelligence: Experience withGNNs,transformers,generative models,Gaussian processes, orreinforcement learning.
  • Cheminformatics: Familiarity withchemical data formats,reaction prediction, and tools such asRDKitorOpenEye.
  • Quantum Mechanics: Practical use ofQM methodsfor synthesis prediction using tools likePSI4,Orca, orGaussian.
  • Big Data: Experience curating and processing data from diverse sources; exposure toApache SparkorHadoopis beneficial.
  • Cloud Platforms: Proficiency withAWS,GCP, orAzure.
  • ML Frameworks: Hands-on withscikit-learn,TensorFlow,PyTorch, or related libraries.

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