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Research Associate in Artificial Intelligence
2 weeks ago
Veselkov's Lab is in search of a skilled and motivated Research Associate to work on projects centred around developing deep learning, reinforcement learning, and graph neural networks. The goal of these projects is to analyse multi-source imaging and omics data in the fields of cancer research and computational medicine. We are seeking a passionate Post-Doctoral Research Associate who will be responsible for designing and implementing novel algorithms to better interpret and interrogate data, with the ultimate aim of improving cancer diagnosis, prognosis, and treatment. If you're a creative thinker with a strong desire for knowledge, we encourage you to apply
**Duties and responsibilities**:
As a member of our multidisciplinary team consisting of clinicians, biologists, and computational scientists, you will have the following key responsibilities and duties:
- Conduct research in the areas of deep learning, reinforcement learning, and graph neural networks for analysing multi-source imaging and omics data in cancer research and computational medicine.
- Develop and implement innovative machine learning algorithms for data interrogation and interpretation of imaging and omics data.
- Integrate imaging and omics data from multiple sources and modalities, including genomics, transcriptomics, proteomics, radiomics, and histopathology.
- Collaborate with other team members, such as radiologists, endoscopists, and computer scientists.
- Present research findings at scientific conferences and publish papers in peer-reviewed journals.
- Contribute to the preparation of grant proposals and progress reports, co-supervise MRes and PhD research projects, and perform appropriate administrative tasks.
**Essential requirements**:
- **Research Associate**: Hold a PhD or equivalent in a relevant numerical discipline, such as computer science, bioinformatics, electrical engineering, biomedical engineering, physics, or a related field.
- ** Research Assistant**: Near completion of a PhD in or equivalent in a relevant numerical discipline, such as computer science, bioinformatics, electrical engineering, biomedical engineering, physics, or a related field.- Strong background in machine learning, specifically deep learning, reinforcement learning, and graph neural networks.
- Proficiency in programming languages like Python and C/C++ and familiar with deep learning frameworks such as PyTorch.
- Experience working with large-scale datasets and preferably developing graphical user interfaces for scientific computing.
- Excellent analytical, communication, and writing skills, and the ability to work effectively as part of a team or independently.
**Further information**:
This post is full time and fixed term for 2 years. You will be based at the Hammersmith Campus (East Acton) and South Kensington Campus.
**Documents**:
- Final JD - MED03805 - GS.pdf
