ABOUT MULTUS

Our mission is to transform human and planetary health by designing cell culture media to fuel the industrial bioeconomy.

We serve companies in the cellular agriculture, advanced therapies and the biopharmaceutical sectors, developing and supplying cell culture media to accelerate their transition from lab to market.

If you are passionate about driving the growth of a sustainable bioeconomy we encourage you to apply and play your part in creating a better future for people and the planet!

ABOUT THE ROLE

This internship offers the opportunity to contribute to a high-impact R&D project at the intersection of machine learning, software engineering, and biotechnology. The work supports the development of computational tools that enhance how we collect, process, and learn from experimental data — helping to improve data quality, consistency, and the speed of our optimisation workflows.

Interns will explore and develop methods that combine software engineering with machine learning to build robust, reusable analytical pipelines. The project involves working with rich experimental datasets and developing approaches to extract reliable, quantitative insights from complex biological data.

This is a genuine blend of software engineering (building well-architected, maintainable systems) and data science/ML (training and evaluating models), making it ideal for candidates who enjoy working across both disciplines.

The role is ideal for students with a strong interest in applied machine learning, software engineering, or data science — particularly in scientific or industrial research contexts.

The internship is a paid fixed-term full-time contract for a minimum of three months, with a flexible start date in summer 2026. We welcome applications from students and recent graduates from any university.

RESPONSIBILITIES

Exploring and evaluating a range of machine learning and analytical approaches to extract quantitative insights from complex biological data

Building reproducible computational pipelines for training, evaluating, and deploying ML models

Working with deep learning architectures and exploring the use of transfer learning to adapt models across different experimental contexts

Developing tooling and infrastructure to support standardised, repeatable analytical workflows

Working with large-scale experimental datasets

Collaborating with cross-functional teams to integrate computational outputs into experimental workflows

SKILLS & EXPERIENCE

Proficiency in Python, with experience writing clean, well-structured, and maintainable code

Familiarity with machine learning and deep learning frameworks such as PyTorch, TensorFlow, or Keras

Proficiency in data manipulation and analysis, including data cleaning, feature engineering, and model evaluation

Experience with version control systems like Git, supporting collaboration and efficient code management

Strong foundation in mathematics and statistics, particularly linear algebra, calculus, and probability theory

Excellent problem-solving and critical thinking abilities, with a capacity to work both independently and as part of a team

Strong communication skills for presenting complex technical concepts to non-technical stakeholders

Ability to demonstrate initiative, proactive problem-solving, and comfort with ambiguity

Enthusiasm for contributing to a fast-paced and interdisciplinary environment, with an eye for detail and code quality

Passion for learning new technologies and a strong curiosity to explore unknown areas

Right to work in the UK

The following skills and experiences would help you stand out even more:

Experience with computer vision or image processing (e.g. OpenCV, scikit-image, or similar)

Familiarity with transfer learning and fine-tuning pre-trained models on domain-specific data

Experience building data pipelines or working with large-scale datasets

Understanding of software engineering best practices: testing, CI/CD, containerisation (e.g. Docker)

Exposure to MLOps tooling for experiment tracking and model management (e.g. MLflow, Weights & Biases)

OUR HIRING PROCESS

Application Closes: Rolling - we will review the applications on a rolling basis

Round 0. Apply online

Round 1. Task

Round 2. 60-minute panel interview to discuss the task and interests

BENEFITS

Salary

25 days' holiday + flexible bank holidays (pro-rata)

Flexible working hours

Collaborative and driven team

Company socials and office snacks

OUR VALUES

TENACITY – WE TRY THINGS WITHOUT THE FEAR OF FAILURE

COLLABORATION – WE WORK TOGETHER INCLUSIVELY, CONSTRUCTIVELY & EFFICIENTLY

CANDOUR – WE TALK TO EACH OTHER WITH RESPECT AND INTEGRITY

OUR ED&I STATEMENT

Multus is an equal-opportunity employer committed to providing a working environment that embraces inclusion, diversity, and belonging. At Multus, we are committed to creating an environment where everyone feels they belong, are enabled to thrive, are respected for who they are, know that they matter, and are empowered to contribute meaningfully. We believe that diverse perspectives and inclusive collaboration drive innovation and make us stronger together.

Multus

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