Computational Chemist & AI Engineer

JR United Kingdom; Greater London; On-site; GBP 50,000 - 90,000; Full time

Job summary

An innovative technology-driven company is on the lookout for an AI Scientist specializing in computational chemistry and machine learning. This role involves developing transformative tools for drug discovery, collaborating with multidisciplinary teams, and translating scientific goals into scalable software solutions. The ideal candidate will possess a strong educational background, advanced programming skills, and a passion for integrating cutting-edge AI technologies into real-world applications. Join this forward-thinking organization to make a significant impact in the life sciences sector, where your expertise will help shape the future of drug discovery.

Qualifications

• MSc or PhD in Computational Chemistry or related fields required.
• Advanced programming skills in Python; experience in C/C++ or Java is a plus.

Responsibilities

• Build relationships with partners, delivering high-impact AI projects.
• Design and implement AI algorithms for drug discovery.

Skills

Computational Chemistry

Applied Machine Learning

Python

C/C++

Java

Artificial Intelligence

Cheminformatics

Quantum Mechanics

Big Data

Cloud Platforms

Education

MSc in Computational Chemistry

PhD in Computational Chemistry

MSc in Cheminformatics

PhD in Cheminformatics

MSc in AI for Scientific Discovery

PhD in AI for Scientific Discovery

Tools

RDKit

OpenEye

PSI4

Orca

Gaussian

Apache Spark

Hadoop

AWS

GCP

Azure

scikit-learn

TensorFlow

PyTorch

Job description

Client:

Skills Alliance

Location:

England, United Kingdom

Job Category:

Other

EU work permit required:

Yes

Job Views:

7

Posted:

18.04.2025

Expiry Date:

02.06.2025

Job Description:

AI Scientist – Computational Chemistry & Machine Learning

A technology-driven company at the forefront of scientific innovation is seeking an AI Scientist with expertise in computational chemistry and applied machine learning to 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 implement cutting-edge AI algorithms, ensuring their integration into robust, production-grade platforms that enhance research efficiency.
• Translate scientific and business goals into scalable and maintainable software solutions.
• Own the full development lifecycle, from requirements gathering through to planning, coding, testing, and deployment.
• Stay current on advancements in computational science and AI, applying relevant innovations to project work.

Core Qualifications

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

Preferred Experience

Expertise in one or more of the following areas:

• Artificial Intelligence: Experience with GNNs, transformers, generative models, Gaussian processes, or reinforcement learning.
• Cheminformatics: Familiarity with chemical data formats, reaction prediction, and tools such as RDKit or OpenEye.
• Quantum Mechanics: Practical use of QM methods for synthesis prediction using tools like PSI4, Orca, or Gaussian.
• Big Data: Experience curating and processing data from diverse sources; exposure to Apache Spark or Hadoop is beneficial.
• Cloud Platforms: Proficiency with AWS, GCP, or Azure.
• ML Frameworks: Hands-on with scikit-learn, TensorFlow, PyTorch, or related libraries.