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PhD studentship: Unlocking the code within the code: Using AI to decipher the role of codon usage in protein synthesis and gene regulation, Cambridgeshire
Client:
Cancer Research UK Cambridge Institute
Location:
Cambridgeshire, United Kingdom
Job Category:
Other
EU work permit required:
Yes
Job Reference:
5199fdce5b56
Job Views:
7
Posted:
03.03.2025
Expiry Date:
17.04.2025
Job Description:
PhD Project: Unlocking the code within the code: Using AI to decipher the role of codon usage in protein synthesis and gene regulation
Please note: This PhD opportunity does not come with a funding award. The successful applicant will need to secure their own funding to finance the course.
Overview
Dr Susanne Bornelöv wishes to recruit a student to work on the project entitled: “Unlocking the code within the code: Using AI to decipher the role of codon usage in protein synthesis and gene regulation”.
This is a unique opportunity for PhD study in the world-leading Cancer Research UK Cambridge Institute (CRUK CI), to start a research career in an environment committed to training outstanding cancer research scientists of the future.
The Institute’s strengths are in genomics, computational biology, and imaging; and significant research effort is currently devoted to cancers arising in the breast, pancreas, brain, and colon. Our Core Facilities provide researchers with access to state-of-the-art equipment, in-house expertise, and training. Scientists at CRUK CI aim to understand the fundamental biology of cancer and translate these findings into the clinic to benefit patients.
There are around 100 postgraduate students at the Cambridge Institute, who play a vital role in its continuing success. We are committed to providing an inclusive and supportive working environment that fosters intellectual curiosity and scientific excellence.
The genetic code contains 61 codons encoding 20 amino acids, and the choice of one synonymous codon over another plays an important role in gene regulation. Some codons slow down translation, which triggers mRNA degradation and halts protein synthesis. Protein synthesis is often dysregulated in cancer, making mRNA translation an attractive therapeutic target.
This project uses artificial intelligence (AI) to unravel the underlying mechanism by which codon-level information regulates translation.
Our group uses computational methods to study the inner workings and control of biological systems. By systematically changing the input mRNA sequence to a model capable of predicting mRNA stability or localization, and analyzing resultant patterns, we can gain understanding of what sequence elements regulate these processes. Additionally, we can use disease-associated alterations as inputs to unravel the underlying mechanism.
These models enable us to conduct experiments on a scale far surpassing what is achievable through traditional methods. The primary challenge lies in making models that accurately capture the complexities of biological systems. In this project, you will use cutting-edge deep learning techniques to address this challenge.
Preferred skills/knowledge
We are looking for someone with a keen interest in AI and deep learning, good computer and coding skills, and a willingness to uncover the fundamental workings of the cell. The ideal candidate will have a degree in computational or systems biology, bioinformatics, computer science, or a related discipline. Applicants with a background in molecular biology or biochemistry and clear evidence of computational skills are also encouraged to apply. The role will offer extensive training in machine learning and computational biology.
How to apply
Please apply via the University Applicant Portal. For further information about the course and to access the Applicant Portal, visit:
https://www.postgraduate.study.cam.ac.uk/courses/directory/cvcrpdmsc
You should select to commence study in Michaelmas Term 2025 (October 2025).
Deadline
The closing date for applications is 31st October 2024 with interviews expected to take place in January 2025.
The University actively supports equality, diversity, and inclusion and encourages applications from all sections of society.
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