The quantitative analysis of biomedical imaging data, especially histology images, will play an increasingly important role in clinical research and diagnostics. The vision and ambition of this research programme is to support projects in computational tissue imaging that help to advance biomedical imaging to link insights in molecular understanding of disease with clinical medicine. You will be developing algorithms that make use of the latest machine learning and computer vision techniques to analyse cell and tissue morphology at different scales. You will be working directly with experts in biomedical image analysis, machine learning, and clinical scientists.
You will:
1. Carry out collaborative projects with colleagues in partner institutions and research groups; be responsible for identifying clinical and clinical research needs through collaborations with pathologists that can be addressed through quantitative imaging.
2. Contribute ideas for new research projects.
3. Be responsible for implementing adequate software solutions that address the collaborative research or the identified clinical needs and process the corresponding data sets. It is expected that you will make effective use of existing algorithm components and collaborations with scientists at the Institute of Biomedical Engineering, Oxford, to develop new solutions where necessary.
4. Contribute to coordinating the bi-monthly project meetings. The post holder will be required to train pathologists (both consultants and pathologists in training), biomedical scientists, and other professional groups as required in the use of the digital pathology equipment and basic principles of the image analysis software.
5. Manage own academic research and administrative activities. This involves small-scale project management to coordinate multiple aspects of work to meet deadlines.
6. Develop ideas for generating research income and present detailed research proposals to senior researchers.
7. Collaborate in the preparation of scientific reports and journal articles and occasionally present papers and posters.
8. Represent the research group at external meetings/seminars, either with other members of the group or alone.
9. According to Section 110 BerlHG, the employee (d/f/m) is provided with time for their own academic qualifications.
Minimum Requirements:
1. Completed university degree (Master).
2. Cooperative and collegial collaboration, independent and team-oriented work.
3. Knowledge of biomedical image analysis, machine learning, and bioinformatics.
4. Passion for interdisciplinary work and implementation of solutions in clinical practice.
5. High degree of independence.
6. Documentation of work, motivation to establish new techniques, independent data analysis, and writing of project reports and manuscripts.
7. Very good command of English.
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