PhD Studentship: Machine Learning: A PhD opportunity in Mathematical Sciences at the University of Nottingham applies artificial intelligence to predict yeast phenotype from genotype, enhancing biotech applications. Collaborating with Phenotypeca, the project aims to identify strains for optimal protein production using novel AI methods. The studentship includes a placement with Phenotypeca, providing valuable industry experience.
Summary Table:
| Start Date | Duration | Location | Closing Date |
|---|---|---|---|
| October 2024 | 4 years | UK Other | Tuesday, January 16, 2024 |
Study Area:
Mathematical Sciences
Scholarship Description:
PhD Studentship: Machine Learning for predicting yeast phenotype from genotype for biotech applications
The project utilizes artificial intelligence to predict yeast phenotype, aiding the identification of strains for optimal protein production. Collaborating with Phenotypeca, the world’s largest yeast strain collection, the research involves exploring various statistical tools and AI models. The studentship includes a three-month placement with Phenotypeca, offering industry exposure in R&D and IT.
Eligibility:
Home and international students with a background in Statistics, Mathematics, Computer Science, Computational Biology, or related disciplines are invited. Strong programming skills in R and/or Python are essential.
Required Documents:
- Curriculum Vitae
- Letter of Intent
- Academic Transcripts
- References
How to Apply:
Check eligibility and submit applications here.
Last Date:
Application deadline: Tuesday, 16 January 2024.
For inquiries, contact Markus Owen at markus.owen@nottingham.ac.uk or bbdtp@nottingham.ac.uk.
