Research Assistant in Deep Learning and Biomedical

4 weeks ago

London, United Kingdom King's College London Full time

Job description

This is a highly collaborative project with several institutions including Oxford University, Cambridge University, and UCL. While having prior experience in working on interdisciplinary projects would be an advantage it is not a requirement.

This post will be offered on an a fixed-term contract for 1 year with the potential for extension

Key responsibilities
- Manage own research and administrative activities, within guidelines provided by senior colleagues
- Select, follow, and adapt experimental protocols
- Gather, analyse, and present scientific data from a variety of sources
- Build and maintain data management systems and data lakes.
- Develop methods for handling heterogeneous types of data
- Develop deep learning algorithms for classification of large biomedical images.
- Contribute to scientific reports and journal articles and the presentation of data/papers at conferences.
- Work in close collaboration with the clinicians to validate the developed methods.
- The above list of responsibilities may not be exhaustive, and the post holder will be required to undertake such tasks and responsibilities as may reasonably be expected within the scope and grading of the post._

Skills, knowledge, and experience

Essential criteria

1. Have MSc in Artificial Intelligence, Biomedical Engineering, Computer Science, Bioinformatics, or another related area.

2. Excellent programming skills in Python.

3. Excellent communication skills, both written and oral, including the ability to write for publication, present research proposals and results, and represent the research group at meetings

4. Good understanding of software testing

5. Demonstrate a strong interest in interdisciplinary research

6. Ability to manage own academic research and associated activities

7. Ability to contribute ideas for new research projects and research income generation

Desirable criteria

1. Experience in dealing with large image data and cloud computing

2. Experience of contributing to reports and articles for publication

4. Experience of working in a research team and contributing ideas for new research projects

5. Experience in large-scale image-based phenotyping in the wider sense.

6. Published research in a relevant field in high profile journals

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