Data Scientist/Machine Learning Engineer - RNA Design

Glasgow
3 weeks ago
Create job alert

About this job

SRG are seeking a highly motivated and skilled data scientist to join our client and to focus on leveraging their proprietary platform to develop novel gene control systems for the cell and gene therapy space. As one of the first hires in this growing company, you will have the unique opportunity to help expand and scale their technology platform and help shape the future of gene therapies.

Our client is a venture-backed biotechnology company that designs novel control mechanisms for the cell and gene therapy market using an innovative AI platform and synthetic biology expertise. The platform enables the design, building and screening of large & complex libraries of RNA-based control systems, to allow the precise control of cell and gene therapies in response to a diverse range of molecules.

Key Responsibilities

Develop and refine AI/ML methods for RNA-based control system development.
Preparation, processing, cleaning, and annotation of datasets tailored for AI development. Manage the curation of these datasets to support various company projects.
Working within a multidisciplinary team, execute data analysis to a high standard and on schedule, to provide accurate data for seamless transition to subsequent project stages, and work closely with team members to inform the design of subsequent experiments.
Design, test and implement algorithms for structural design space exploration.
Demonstrate strong teamwork and a focus on achieving shared goals with a commitment to high-quality outcomes.

Skills

Essential

Proven track record in the successful development and deployment of AI/ML-based tools.
Strong command over Python and major ML frameworks such as Keras, PyTorch, TensorFlow, or Scikit-Learn.
Extensive experience in building and implementing predictive models to design biological sequences and/or analyse biological sequence data (DNA, RNA or protein).
Strong ability to communicate complex technical concepts effectively and collaborate closely with both experimental biologists and computational scientists.
Exceptional analytical skills with a methodical approach to problem-solving.

Desirable

Familiarity with handling and analysing Next-Generation Sequencing (NGS) data.
Skilled in using cloud platforms for deploying and managing ML applications.
Advanced ML Deployment: Experience in designing and rolling out large-scale machine learning algorithms.

Qualifications

PhD/MSc (or equivalent professional experience) in data science/AI, computer science, bioinformatics or other related field.Carbon60, Lorien & SRG - The Impellam Group STEM Portfolio are acting as an Employment Business in relation to this vacancy

Related Jobs

View all jobs

Machine Learning Engineer, London

Staff Data Scientist

Head of Data Science

Computational Biology & Machine Learning Scientist

Computational Biology & Machine Learning Scientist

Computational Biology & Machine Learning Scientist

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Rural-Remote Machine Learning Jobs: Finding Balance Beyond the Big Cities

Over the past decade, machine learning (ML) has transformed from a niche research domain into a pervasive technology underpinning everything from recommendation systems and voice assistants to financial forecasting and autonomous vehicles. Historically, the UK’s major tech hubs—particularly London—have been magnets for top ML talent and corporate headquarters. However, remote work has become mainstream, and many ML professionals are realising they can excel in their field while living far beyond the city limits. At MachineLearningJobs.co.uk, we’ve observed a growing interest in positions that allow for a rural lifestyle or a coastal environment, often reflected in search terms like “ML remote countryside” or “tech jobs by the sea.” This surge is no coincidence. Flexible work policies, better rural broadband, and the nature of machine learning tasks—much of which can be done through cloud platforms—are bringing new opportunities to those who wish to swap urban hustle for fresh air and scenic views. Whether you’re a data scientist, ML engineer, researcher, or product manager, a rural or seaside move could reinvigorate your work-life balance. In this article, we’ll unpack why rural-remote ML jobs are on the rise, how you can navigate the challenges of leaving the city, and what you need to do to thrive in a machine learning career beyond the M25. If you’ve dreamt of looking up from your laptop to rolling fields or ocean waves, keep reading—your rural ML role might be closer than you think.

Quantum-Enhanced Machine Learning—Propelling AI into the Next Frontier

Machine learning (ML) has revolutionised how we interpret data, build predictive models, and create intelligent applications. From recommendation engines and self-driving cars to advanced genomics and natural language processing, ML solutions are integral to nearly every corner of modern life. However, as data complexity and model size continue to skyrocket, the computational demands placed on ML systems grow in tandem—often pushing even high-performance classical computers to their limits. In recent years, quantum computing has emerged as a tantalising solution to these challenges. Unlike traditional digital systems, quantum computers exploit quantum mechanics—superposition and entanglement—to process information in ways that defy conventional logic. As these machines mature, they promise exponential speed-ups for certain tasks, potentially reshaping how we approach AI and data-intensive challenges. What does this mean for machine learning? Enter quantum-enhanced ML, a new frontier where quantum processors and classical ML frameworks unite to accelerate model training, tackle high-dimensional data, and solve complex optimisation tasks more efficiently. In this article, we will: Unpack the current state of machine learning, highlighting key bottlenecks. Provide a concise overview of quantum computing—why it’s radical and how it differs from classical technology. Examine potential breakthroughs in quantum-enhanced ML, including real-world use cases and technical approaches. Explore the roles and skill sets that will define this quantum-AI era, with guidance on how to prepare. Discuss the roadblocks (like hardware maturity and ethical concerns) and how they might be addressed in the years to come. If you’re a machine learning engineer, data scientist, or simply an AI enthusiast fascinated by the next wave of computational innovation, read on—quantum computing could become an integral part of your future toolkit, opening up job opportunities and reimagining what ML can achieve.

Machine Learning Jobs at Newly Funded UK Start-ups: Q3 2025 Investment Tracker

Machine learning (ML) has become the beating heart of modern tech innovation, powering breakthroughs in healthcare, finance, cybersecurity, robotics, and more. Across the United Kingdom, this surge in ML-driven solutions is fueling the success of countless start-ups—and spurring demand for talented machine learning engineers, data scientists, and related professionals. If you’re eager to join a high-growth ML company or simply want to keep tabs on the latest trends, this Q3 2025 Investment Tracker will guide you through the newly funded UK start-ups pushing the boundaries of ML. In this article, we’ll highlight key developments from Q3 2025, delve into the most promising newly funded ventures, and shed light on the machine learning roles they’re urgently seeking to fill. Plus, we’ll show you how to connect with these employers via MachineLearningJobs.co.uk, a dedicated platform for ML job seekers. Let’s dive in!