Postdoctoral Research Associate

We are seeking to recruit a Post-Doctoral Research Associate to act as a researcher for a project funded by BBSRC, titled Joint data- and model-driven attention-based integration of imaging, proteomics, and metabolic modelling.

This is a large collaborative project between three organisations, aiming to develop methodology at the intersection of deep learning, metabolic modelling, and multi-omics, on a concrete biotechnology case study.

The main objective is to design and implement an attention-based multi-modal deep learning architecture to:

- Integrate imaging, proteomics and metabolic modelling into a unified deep learning framework.

- Obtain multi-modal predictors of the outcome of F. venenatum fermentation campaigns.

The data will be newly collected as part of the project by the wider team, which also includes a lab technician. This post will specifically focus on the computational, modelling and deep learning aspects, with a view to collaboratively obtaining lab validation of the predictions as part of the project and the wider delivery team.

By joining this project, you will be part of and supported by the larger interdisciplinary Angione lab (https://sites.google.com/view/angionelab/). For this project, the post holder will work with the team led by Prof Claudio Angione (Teesside), Prof Peter O'Toole (York), Dr Annalisa Occhipinti (Teesside), Dr Gillian Taylor (National Horizons Centre), and Dr Nanda Puspita (Marlow Ingredients, Quorn).

PhD degree in computer science, bioinformatics, mathematics, physics, engineering (or related subjects), with related experience and with the relevant technical, professional or specialist knowledge to carry out the role.
Previous research and implementation experience in deep learning, with an interest in applying it to biomedicine., Disability Confident
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