Multus
Multus is offering an exciting Industrial Placement opportunity for a talented Imperial MSc or MEng student passionate about applying the latest advances in computer science and AI to solve challenges in engineering biology. We are a rapidly growing biotech company on a mission to make cultivated meat more affordable and accessible by developing animal-free, food-grade growth media using optimized proteins.
As a member of our engineering team, you’ll play an active role in shaping our technical direction and have hands-on exposure to cutting-edge technologies in both computational and biotech lab settings. This role offers an excellent opportunity to work with state-of-the-art machine learning methods, automation systems, high-throughput screening, and more.
Please note this role is only open for Imperial students.
Role & Responsibilities:
· Advanced Surrogate Modeling: Contribute to enhancing machine learning models for predicting biological outcomes, with the potential to explore and implement novel techniques for better model fitting and sensitivity analysis.
· Multi-Objective Optimization: Work on optimization problems involving multiple simultaneous objectives, such as cell growth, morphology, and production cost, across various biological systems. Explore efficient computational strategies to balance and optimize these competing factors.
· Formulation Simplification & Optimization: Assist in developing approaches to streamline complex biological formulations by reducing ingredient count while maintaining or enhancing performance. This may involve gradient-based methods and improving algorithmic efficiency.
· Leveraging Prior Experimental Data: Utilize and develop transfer learning methods to improve the use of existing data from our experiments, speeding up the development and optimization of new projects.
· Algorithm Development for Ingredient Screening: Play a role in advancing our computational tools for systematically identifying key factors from large sets of possible ingredients, improving the selection process for optimal experimental conditions.
· Integration of Computational and Lab-Based Approaches: Contribute to the conceptualization and execution of wet-lab experiments, working closely with the team to integrate computational insights into lab-based processes and methodologies.
Essential Skills:
· Proficiency in data manipulation and analysis, including data cleaning, feature engineering, and model evaluation.
· Strong foundation in mathematics and statistics, particularly linear algebra, calculus, and probability theory.
· Experience with version control systems like Git, supporting collaboration and efficient code management.
· 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.
Preferred Skills:
· Hands-on experience with machine learning and deep learning frameworks, such as TensorFlow, PyTorch, Keras, or JAX.
· Background in probabilistic modeling, with familiarity in techniques like Gaussian processes or Bayesian optimization.
Added Advantage:
· Exposure to Gaussian processes and Bayesian optimization frameworks and multi-objective problem-solving.
· Understanding of techniques for model evaluation, parameter sensitivity analysis and decomposition.
Placement Open To:
· MSc Artificial Intelligence, Department of Computing (4 months: ~6th May – ~2nd September, 2025)
· MSc Artificial Intelligence Applications and Innovation, Imperial-X (4 months: ~6th May – ~2nd September, 2025)
Salary and Benefits:
· Paid internship
· Opportunity to work with state-of-the-art technologies in life sciences and data science.
· Pro rata flexible PTO policy with 25 paid holidays per year .
· Flexible working location and hours.
· Access to ultra-high-performance computing resources.
· A supportive and collaborative team environment, fostering growth and development.
· The chance to be part of a company making a real impact in the sustainability
