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Computational Chemist & AI Engineer

Skills Alliance
Southampton
6 months 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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Quantum Computing Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK quantum computing hiring has shifted from credential‑first screening to capability‑driven evaluation. Employers now value provable contributions across the stack—algorithms & applications, compilation & optimisation, circuit synthesis, control & calibration, hardware characterisation, error mitigation/correction (QEM/QEC), verification/benchmarking, and hybrid HPC/quantum workflows—plus the ability to communicate trade‑offs, costs and feasibility to non‑quantum teams. This guide explains what’s changed, what to expect in interviews and how to prepare—especially for quantum algorithm engineers, quantum software/compilers, experimentalists, quantum control & firmware, cryo/readout engineers, quantum error correction researchers, verification/benchmarking specialists, and quantum‑adjacent product managers. Who this is for: Quantum algorithm/applications engineers, compiler/optimisation engineers, control/firmware engineers, experimental physicists & hardware engineers (superconducting, trapped ion, photonic, spin/neutral atom), cryogenics & RF/microwave, QEC researchers, verification/benchmarking specialists, quantum‑HPC orchestration engineers, and product/BD roles in the UK quantum ecosystem.

Why Quantum Computing Careers in the UK Are Becoming More Multidisciplinary

Quantum computing has long been considered an elite subfield of physics and computer science. But as quantum technologies advance—from fault-tolerant hardware to quantum algorithms and quantum cryptography—they’re moving closer to real applications in finance, materials simulation, optimisation, cryptography and more. As this transition happens, UK quantum computing careers are becoming increasingly multidisciplinary. Quantum systems are no longer just the domain of physicists and quantum software engineers. If quantum technologies are to be trusted, adopted and regulated, professionals must also incorporate expertise in law, ethics, psychology, linguistics & design. In practice, quantum computing projects now intersect with data governance, risk, human interaction, explainability and communication. In this article, we’ll explore why quantum computing careers in the UK are shifting to multidisciplinary roles, how these five supporting fields intersect with quantum work, and what job-seekers & employers should do to keep up in this evolving frontier.

Quantum Computing Team Structures Explained: Who Does What in a Modern Quantum Department

Quantum computing has shifted from lab curiosity to the next frontier of high-impact computing. Across the UK, universities, national labs, start-ups, and established tech and finance firms are building quantum teams to explore algorithms, design hardware, and deliver quantum-ready software. As momentum grows, so does the need for clear, robust team structures. Because quantum R&D spans physics, engineering, computer science, and product, ambiguity about who does what can slow progress, increase risk, and inflate costs. This guide maps the typical roles in a modern quantum computing department, how they collaborate across the research-to-product lifecycle, skills and backgrounds UK employers expect, indicative salary ranges, common pitfalls, and practical ways to structure teams that move fast without breaking science.