SRG - Data Scientist / Machine Learning Engineer – RNA Design

Bionow; Glasgow; On-site; GBP 45,000 - 75,000; Full time

Job summary

A forward-thinking biotechnology company is seeking a passionate Data Scientist/Machine Learning Engineer to join their innovative team. In this pivotal role, you will leverage cutting-edge AI technology to develop novel gene control systems, working closely with experts in synthetic biology. This is a unique opportunity to contribute to groundbreaking advancements in cell and gene therapy, where your expertise in AI/ML will directly impact the future of therapeutic solutions. If you're eager to make a difference in a dynamic environment, this role is perfect for you.

Qualifications

• PhD or MSc in relevant fields such as data science, AI, or bioinformatics.
• Experience in developing AI/ML tools and predictive models.

Responsibilities

• Develop and refine AI/ML methods for RNA-based control systems.
• Manage datasets for AI development and execute high-standard data analysis.
• Collaborate with multidisciplinary teams to inform experimental designs.

Skills

AI/ML Development

Python

Keras

PyTorch

TensorFlow

Scikit-Learn

Predictive Modeling

Next-Generation Sequencing (NGS) Data Analysis

Cloud Platforms

Analytical Skills

Education

PhD in Data Science/AI

MSc in Computer Science

Experience in Bioinformatics

Job description

Job Title: Data Scientist / Machine Learning Engineer – RNA Design Category: Technical roles Closing Date: 30/05/2025

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

• 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.
• 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 experiencein data science/AI, computer science, bioinformatics or other related field.

If you meet the above requirements, please send your CV to [e-mail]