PhD studentship: Artificial intelligence based early detection of signet ring cell carcinoma in hereditary diffuse gastric cancer patients
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 has excellent state-of-the-art facilities and research ranges from basic biology and computational biology through to translational cancer research and clinical application.
Postgraduate students play a pivotal role in the continuing success of our research programmes. If you are interested in contributing to our success, please find further information at: https://www.cruk.cam.ac.uk/jobs-and-studentships/postgraduate-study
Professor Florian Markowetz wishes to recruit a student to work on the project entitled: Artificial intelligence based early detection of signet ring cell carcinoma in hereditary diffuse gastric cancer patients
This project will be co-supervised by Dr. Massimiliano di Pietro, a consultant gastroenterologist at Addenbrookes' hospital.
For further information about the research groups, including their most recent publications, please visit their website:
www.cruk.cam.ac.uk/research-groups/markowetz-group/
www.earlycancer.cam.ac.uk/dr-massimiliano-di-pietro/
Project details
Hereditary diffuse gastric cancer (HDGC) is a syndrome predisposing individuals to gastric cancer linked to mutation of the e-Cadherin gene (CDH1). Guidelines recommend prophylactic surgery with the view to prevent disease specific mortality, however a gastrectomy is linked to significant morbidity and impacts negatively to quality of life. Therefore, recently endoscopic surveillance has been proposed to assess the level of risk and detect early cancer, so that the best timing of prophylactic surgery is decided. Early signet ring cell carcinoma, however, is difficult to diagnose on standard endoscopy as the endoscopic features are very subtle. There is variation in practice in the pathological yield of biopsies even among expert centres. The aim of this project is to test and validate machine learning and deep learning methods to improve the diagnosis of early cancer in individuals with HDGC. This project is expected to lead to the development of an AI system that can assist the physician to diagnose early signet ring cancer, with high accuracy, during endoscopic surveillance of individuals with HDGC, ultimately improving the diagnosis of of sporadic gastric cancer.
Preferred skills/knowledge
We welcome applicants from both a computational or clinical background. Preferably, applicants have prior experience in computer programming and be familiar with data analysis, especially imaging data, in a programming language used for deep learning such as Python, including libraries such as Scikit-learn or PyTorch, and be passionate about the application of AI in clinical practice.
References/Further reading (optional)
- Lee CYC, Olivier A, Honing J, et al. Endoscopic surveillance with systematic random biopsy for the early diagnosis of hereditary diffuse gastric cancer: a prospective 16-year longitudinal cohort study. Lancet Oncol. 2023;24(1):107-116.
- Blair VR, McLeod M, Carneiro F, et al. Hereditary diffuse gastric cancer: updated clinical practice guidelines. Lancet Oncol. 2020;21(8):e386-e397.
- Li J, Zhu Y, Dong Z, et al. Development and validation of a feature extraction-based logical anthropomorphic diagnostic system for early gastric cancer: A case-control study. EClinicalMedicine. 2022;46:101366.
- Dong Z, Wang J, Li Y, et al. Explainable artificial intelligence incorporated with domain knowledge diagnosing early gastric neoplasms under white light endoscopy. NPJ Digit Med. 2023;6(1):64.
Funding
This four-year studentship is funded by Cancer Research UK and includes full funding for University and College fees and, in addition, a stipend currently of £21,000 per annum for 4 years.
Eligibility
No nationality restrictions apply to Cancer Research UK studentships. Applications are invited from recent graduates or final year undergraduates who hold or expect to gain a first/upper second-class degree (or equivalent) in a relevant subject from any recognised university worldwide. Applicants with relevant research experience gained through Master¿s study, or while working in a laboratory, are strongly encouraged to apply.
How to apply
Please apply using the University Applicant Portal. For further information about the course and to access the applicant portal, go to:
https://www.postgraduate.study.cam.ac.uk/courses/directory/cvcrpdmsc
Please select to commence study in Michaelmas Term 2024 (October 2024).
To complete your online application, you will need to provide the following:
Reference Request
The names and contact details of two academic referees who have agreed to act on your behalf.
Course Specific Question
Your statement of interest (limit of 2,500 characters) should explain why you wish to be considered for the studentship and which qualities and experience you will bring to the role.
Supporting Document
Please upload your CV (PDF file).
Deadline
The closing date for applications is 31 March 2024 with interviews expected to take place in mid to late May.
Please quote reference SW40762 on your application and in any correspondence about this vacancy.
The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.
The University has a responsibility to ensure that all employees are eligible to live and work in the UK.
PhD studentship: Identifying morphological progression risk factors in oesophageal cancer by combining genome sequencing with histopathology using deep neural networks
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 has excellent state-of-the-art facilities and research ranges from basic biology and computational biology through to translational cancer research and clinical application.
Postgraduate students play a pivotal role in the continuing success of our research programmes. If you are interested in contributing to our success, please find further information at: https://www.cruk.cam.ac.uk/jobs-and-studentships/postgraduate-study
Professor Florian Markowetz wishes to recruit a student to work on the project entitled: Identifying morphological progression risk factors in oesophageal cancer by combining shallow whole genome sequencing and histopathology using deep neural networks.
For further information about the research group, including their most recent publications, please visit their website: www.cruk.cam.ac.uk/research-groups/markowetz-group/
Project details
Early detection of risk factors for oesophageal cancer can dramatically increase the survival rate for patients. Doctors often rely on numerous data sources to conclude a diagnosis, including medical history and pathology results. There is evidence that genomic data alone can predict the progression of cancer years before visible symptoms present themselves, however current computational risk prediction methods often only utilise one modality, e.g. histopathology images, or patient data. This project will aim to integrate these multi-modal features for risk prediction of oesophageal cancer by understanding the relationship between genomic data from biopsies, and anonymised patient medical history.
Preferred skills/knowledge
Coding experience and knowledge is essential, preferably in Python. Experience with associated image processing libraries, or PyTorch and other deep learning libraries is preferred.
References/Further reading (optional)
Killcoyne, S., Gregson, E., Wedge, D.C. et al. 'Genomic copy number predicts esophageal cancer years before transformation.' Nat Med 26, 1726-1732 (2020). doi:10.1038/s41591-020-1033-y Mandair, Divneet, Jorge S. Reis-Filho, and Alan Ashworth. 'Biological Insights and Novel Biomarker Discovery through Deep Learning Approaches in Breast Cancer Histopathology'. Npj Breast Cancer 9, 21 (2023), https://doi.org/10.1038/s41523-023-00518-1.
Funding
This four-year studentship is funded by Cancer Research UK and includes full funding for University and College fees and, in addition, a stipend currently of £21,000 per annum for 4 years.
Eligibility
No nationality restrictions apply to Cancer Research UK studentships
Applications are invited from recent graduates or final year undergraduates who hold or expect to gain a first/upper second-class degree (or equivalent) in a relevant subject from any recognised university worldwide. Applicants with relevant research experience gained through Masters study, or while working in a laboratory, are strongly encouraged to apply.
How to apply
Please apply using the University Applicant Portal. For further information about the course and to access the applicant portal, go to:
https://www.postgraduate.study.cam.ac.uk/courses/directory/cvcrpdmsc
Please select to commence study in Michaelmas Term 2024 (October 2024).
To complete your online application, you will need to provide the following:
Reference Request
The names and contact details of two academic referees who have agreed to act on your behalf.
Course Specific Question
Your statement of interest (limit of 2,500 characters) should explain why you wish to be considered for the studentship and which qualities and experience you will bring to the role.
Supporting Document
Please upload your CV (PDF file).
Deadline
The closing date for applications is 31 March 2024 with interviews expected to take place mid to late May.
Please quote reference SW40760 on your application and in any correspondence about this vacancy.
The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.
The University has a responsibility to ensure that all employees are eligible to live and work in the UK.
PhD studentship: Dietary modulation of amino acids to improve chemotherapy response in breast cancer
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 has excellent state-of-the-art facilities and research ranges from basic biology and computational biology through to translational cancer research and clinical application.
Postgraduate students play a pivotal role in the continuing success of our research programmes. If you are interested in contributing to our success, please find further information at: https://www.cruk.cam.ac.uk/jobs-and-studentships/postgraduate-study
Professor Greg Hannon and Dr Kirsty Sawicka wish to recruit a student to work on the project entitled: Dietary modulation of amino acids to improve response to chemotherapy in breast cancer.
For further information about the research group, including their most recent publications, please visit https://www.cruk.cam.ac.uk/research-groups/hannon-group.
Project details
An opportunity has arisen for a talented student to join the interdisciplinary laboratory of Professor Greg Hannon located at the CRUK Cambridge Institute, University of Cambridge. The Hannon laboratory has a long-standing interest in RNA biology and cancer research, and a strong history of developing new tools to address cutting-edge questions in these fields. The lab has lead the way in spatial imaging of tumours and established a suite of technologies to interrogate tumour heterogeneity and the tumour microenvironment.
The successful applicant will work as part of a small, collaborative team of scientists in the Hannon lab working on tumour heterogeneity and will be supported by a fully-funded PhD studentship from Breast Cancer Now. Previous work in the lab has identified a subpopulation of triple negative breast cancer cells that are resistant to standard chemotherapy and which are highly dependent on non-essential amino acids. This project will build upon these findings and use pre-clinical and patient-derived models of breast cancer to study the effects of modulating the availability of specific amino acids through drugs or dietary changes on tumour growth and response to chemotherapy. The ultimate aim of project is to develop novel and more effective treatments for triple negative breast cancer and identify biomarkers of response to these interventions. Over the course of the project, the successful applicant will utilise a range of cutting-edge technologies including single cell lineage tracing and transcriptomics methods developed in the Hannon lab to bring new insights into the effects of diet on the success of cancer therapies. There will be additional opportunities alongside this project to engage in the development of new clonal lineage tracing and multi-omics methods.
Preferred skills/knowledge
The ideal candidate would have a strong background in genetics, molecular biology and/or biochemistry, with an interest in cancer therapies, technology development, cancer biology and single cell sequencing-based methods. A minimum of 6 months of practical research experience is required, preferably in molecular biology. The successful candidate is expected to drive their own independent research project while also working closely with other team members. Excellent communication, record keeping, organisational, time-management and problem-solving skills are required. The project will involve mouse models and bioinformatics - no prior experience in these areas is required as all necessary training will be provided, but a willingness to learn is essential.
Further Reading
- Wild SA, et al. (2022). Clonal transcriptomics identifies mechanisms of chemoresistance and empowers rational design of combination therapies. Elife.
- Maddocks ODK, et al. (2017). Modulating the therapeutic response of tumours to dietary serine and glycine starvation. Nature.
- LeBoeuf SE et al. (2020). Activation of Oxidative Stress Response in Cancer Generates a Druggable Dependency on Exogenous Non-essential Amino Acids. Cell Metab.
Funding
This position is funded by a Breast Cancer Now studentship to Prof. Hannon and Dr Sawicka and includes full funding for University and College fees and in addition, a stipend currently of £21,000 per annum for 4 years.
Eligibility
No nationality restrictions apply. Applications are invited from recent graduates or final year undergraduates who hold or expect to gain a first/upper second-class degree (or equivalent) in a relevant subject from any recognised university worldwide. Applicants with relevant research experience, gained through Master's study or work in a laboratory environment, are strongly encouraged to apply.
How to apply
Please apply using the University Applicant Portal. For further information about the course and to access the applicant portal, go to:
https://www.postgraduate.study.cam.ac.uk/courses/directory/cvcrpdmsc
Please select to commence study in Michaelmas term 2024 (October 2024).
To complete your on-line application, you need to provide the following:
Reference Request: The names and contact details of two academic referees who have agreed to act on your behalf.
Course Specific Question: Your statement of interest (limit of 2,500 characters) should explain why you wish to be considered for the studentship and which qualities and experience you will bring to the role. Please also state how you learned of the studentship.
Supporting Document: Please upload your CV (PDF file), which should include a list of the examinations taken at undergraduate level and if possible, your examination results.
Deadline
The closing date for applications is 12 March 2024 with interviews expected to take place in the week beginning either 20 or 27 March 2024.
Please quote reference SW40499 on your application and in any correspondence about this vacancy.
The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.
The University has a responsibility to ensure that all employees are eligible to live and work in the UK.
Astra Zeneca funded Non clinical PhD Studentship (Fixed Term) in `Multimodal AI-guided tools for early prediction of disease progression in neurodegenerative disorders'.
Applications are invited for 4-year PhD studentship based in the Department of Psychology, University of Cambridge and the new AstraZeneca Discovery Centre at Cambridge. The student will be working on a collaborative project jointly supervised by Professor Zoe Kourtzi at Department of Psychology Cambridge in collaboration with AstraZeneca's Neuroscience (Dr Keith Tan, Dr Andrew Lowe) and Data Science & AI (Dr Philip Teare, Dr Gayathri Mohankumar) teams and will work have opportunity to work across the two sites. The project, entitled 'Multimodal AI-guided tools for early prediction of disease progression in neurodegenerative disorders' is in the field of AI for Neuroscience that has generated much excitement in both academia and industry.
The project focuses on the development and implementation of AI-guided approaches for early prediction of neurodegenerative disorders. In particular, we aim to develop an innovative data-driven approach that capitalises on state-of-the-art algorithms from artificial intelligence (foundational models) to mine multimodal data from polygenic risk scores, MRI scans, biomarkers and cognitive tasks for early prediction of disease progression. Using this cross-disciplinary approach, we will develop AI-guided tools that predict individualised disease trajectories. We will optimise and validate these tools using large-scale research data and real-world data from clinical trials to assess their efficacy in identifying the right patients for the right treatment.
Candidate
We are looking for a highly motivated and enthusiastic individual capable of thinking and working independently. Applicants should have or shortly expect to obtain a first or upper second-class degree from a UK university, or an equivalent standard from an overseas university, in a relevant subject such as Maths, Computer Science, Engineering, Neuroscience, Medicine. Experience with machine learning, data science, bioinformatics, clinical data analytics is desirable and background or strong interest in neuroscience and neurodegeneration preferable.
The position is open to UK citizens or overseas students who meet the UK residency requirements (home fees) or are able to augment the funds to cover the extra costs associated with international student fees through scholarships or funding schemes. Full details of the University's entrance requirements and scholarships are specified on the following link: https://www.postgraduate.study.cam.ac.uk/
Funding Full funding covering Maintenance fees at £21,500 per annum and the University Composition Fee is provided for the studentship, with effect from 1 October 2024.
Fixed-term: The funds for this post are available for 4 years in the first instance.
Application Process You can find out more about the Department of Psychology at https://www.psychol.cam.ac.uk/ and Please address any questions about this studentship to Professor Zoe Kourtzi at zk240@cam.ac.uk
Applications for this studentship should be made to the Department of Psychology. The course code is BLPC22 (PhD in Psychology). https://www.postgraduate.study.cam.ac.uk/application-process/how-do-i-apply
With your application you will be required to submit (i) a draft research proposal outlining your suitability, why you are interested in pursuing a PhD in this area, your background and research interests. (ii) your CV stating your citizenship and years of residence in the UK (If applicable) (iii) copies of your academic transcripts (iv) details of two academic referees.
Student support and training As a postgraduate student at Cambridge, you will have access to a wide range of training opportunities and benefit from close supervision provided by a primary and secondary PhD supervisor as well as a personal mentor. The collaboration between teams (Kourtzi, AstraZeneca) will provide you with unique cross-disciplinary training in discovery and translational neuroscience, as well as experience in translating research to industry and clinical practice.
During the PhD, there is no taught or examined coursework, but students are encouraged to attend the wide variety of lectures and training courses available to them across the Institute and wider University. This includes a centrally run Statistics course and the University Core Skills Training Programme, which includes sessions on Time Management, Presentation and Performance and Scientific Writing. Students at the Institute will be members of the University's Postgraduate School of Life Sciences (PSLS) who offer a wide variety of core skills and professional development training. Visit the Researcher Development page on the PSLS website for more information. In addition, the student can also take advantage of training courses and seminars in therapeutic sciences offered by Cambridge Academy of Therapeutic Sciences.
All students are expected to attend all internal and external seminars held within the Department of Psychology. Students will also be encouraged to attend and present at the annual AstraZeneca students symposium.
Diversity and Inclusion
The University actively supports equality, diversity and inclusion and encourages applications from all sections of society. We place major emphasis on the importance of team work and an enjoyable work environment as a foundation for performing internationally leading research. This will allow the student to acquire cutting edge research methodologies in a supportive environment, where they can focus on making the best possible scientific progress.
The closing date for applications will be Sunday 18 February 2024 at midnight.
Interviews will take place February/March 2024
Please quote reference PJ40357 on your application and in any correspondence about this vacancy.
The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.
The University has a responsibility to ensure that all employees are eligible to live and work in the UK.
