We are seeking a researcher with expertise in computer vision and chemistry to work in collaboration with Unilever to design computer vision-enhanced workflows for automated sustainable consumer goods formulation. Formulation is a high-dimensional search problem that requires the combination of quantitative and qualitative measurements. Despite huge advances in workflow automation, this process is overwhelmingly done by hand, driven by manual search through parameter space. This limitation is in large part due to the challenges in integrating qualitative and quantitative assessment into complex multi-step formulation workflows.
Emerging computer vision techniques underpinned by convolutional neural networks (‘CNNs’) have enormous potential to be integrated into automated formulation workflows, transforming the speed and efficiency of the process. In this project, you will adapt established CNN-based computer vision methods for soft matter sample classification developed in the Forth group into automated workflows deployed at Unilever. Working with both the Forth group and formulation and automation experts at Unilever, you will develop model systems to explore computer-vision-based classifier performance, integrate output data into Unilever data handling platforms, and develop closed-loop workflows that design future experiments based on past results.
The project would suit scientists with experience of both benchtop and digital chemistry who are motivated by working in a collaborative, industry-facing environment. You will work in a highly collaborative environment involving academic and industry partners and will require excellent communication skills and the ability to engage effectively with a diverse range of stakeholders.
Commitment to Diversity
The University of Liverpool is committed to enhancing workforce diversity. We actively seek to attract, develop, and retain colleagues with diverse backgrounds and perspectives. We welcome applications from all genders/gender identities, Black, Asian, or Minority Ethnic backgrounds, individuals living with a disability, and members of the LGBTQIA+ community.
