Are you passionate about leveraging machine learning to make a profound impact on cancer research? Join the world-leading Ovarian Cancer Programme at the CRUK Cambridge Centre, University of Cambridge as a Postdoctoral Researcher and contribute to cutting-edge advancements in the understanding and treatment of ovarian cancer. These exceptional positions offer a unique opportunity to work with diverse data types, including radiological imaging, genomics, liquid biopsies, and digital pathology. You will work at the forefront of innovation, shaping the future of cancer research.
The Research Focus
You will be part of a pioneering effort to unravel the complexities of ovarian cancer through the integration of machine learning techniques and multi-omics data analysis. Your research will bridge various data modalities, including radiological imaging, genomics, liquid biopsies, and digital pathology, to identify novel biomarkers, uncover disease mechanisms, and develop personalized therapeutic approaches.
Your research will be supervised by Prof. James Brenton and Dr Mireia Crispin. The work will span several projects and collaborations with academic and industrial partners, within the UK and overseas.
Key Responsibilities and Duties
- Conduct innovative research in machine learning and data analysis, focusing on the integration and interpretation of diverse data types relevant to ovarian cancer.
- Collaborate closely with a multidisciplinary team of clinicians, biologists, and computational scientists to develop advanced algorithms and models.
- Apply machine learning techniques to analyze and extract meaningful insights from medical imaging, genomics, liquid biopsy, and/or digital pathology data.
- Identify predictive biomarkers, molecular subtypes, and potential therapeutic targets using state-of-the-art computational methods.
- Contribute to the development of open-source tools and pipelines to facilitate data analysis and knowledge sharing within the research community.
- Publish research findings in high-impact scientific journals and present at international conferences.
Requirements and Qualifications
- A Ph.D. in a relevant field such as Computer Science, Bioinformatics, Computational Biology, or a related discipline.
- Strong background and expertise in machine learning, data mining, or statistical - Proficiency in programming languages such as Python, R, or MATLAB, with experience in utilizing relevant libraries and frameworks.
- Familiarity with at least one of the data types of interest, and the ability to integrate and analyze these data modalities.
- Knowledge of cancer biology, molecular oncology, and familiarity with ovarian cancer research is advantageous.
- Excellent communication and collaboration skills, enabling effective interaction with a diverse team of researchers and clinicians.
Benefits and Advantages
- Join a vibrant and collaborative research environment with access to cutting-edge facilities, extensive datasets, and state-of-the-art technologies.
- Work under the mentorship and guidance of an experienced team that is globally recognized in the field of ovarian cancer research.
- Contribute to a programme that is dedicated to making a meaningful impact on ovarian cancer treatment and patient outcomes.
- Showcase your research findings through publications, conferences, and collaborations, establishing a strong foundation for a successful scientific career.
- Competitive salary and benefits package from the University of Cambridge commensurate with academic standards, providing support for your professional growth.
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