Research Scientist (Machine Learning)

NLP PEOPLE
London
3 months ago
Applications closed

Related Jobs

View all jobs

Research Scientist (Machine Learning), London

Research Scientist, Machine Learning

Research Scientist (Quantum Chemistry and Machine Learning), London London

Research Scientist (Machine Learning), London London

Senior Research Scientist: Data Science and Machine Learning AIP

AI Research Scientist — Deep Learning & LLMs (Hybrid)

Overview

We’re looking for aResearch Scientist (Machine Learning)to join an ambitious and interdisciplinary team applying AI to transform drug discovery and accelerate the development of life-changing medicines.

This is a chance to work on cutting-edge ML research with direct real-world impact, in a collaborative environment where innovation and creativity are encouraged.

This role will off you

  • Work at the intersection of AI and life sciences with high-impact applications.
  • Hybrid working (3 days per week in the London office).
  • A collaborative, inclusive culture with opportunities for growth and leadership.
What you’ll do
  • Design and develop novel ML models and algorithms.
  • Apply deep learning and generative modelling to complex scientific problems.
  • Collaborate with experts across biology, chemistry, physics, and engineering.
  • Analyse, tune, and optimise experimental results.
  • Depending on experience: lead projects, mentor others, and shape research strategy.
What you’ll bring
  • PhD (or equivalent experience) in ML, computer science, or a related field.
  • Proven expertise in deep learning research and model development.
  • Strong knowledge of mathematics (linear algebra, calculus, statistics).
  • Experience with ML frameworks such as PyTorch, TensorFlow, or JAX.
  • A passion for applying ML to real-world scientific challenges.
Nice to have
  • Experience working with biological or chemical data.
  • Familiarity with large-scale deep learning, generative models, GNNs, RL, or computer vision.
  • Contributions to publications, research projects, or open-source ML.


#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.