Research Scientist - Computational Biologist
This role involves developing image analysis tools for the analysis of gastrointestinal (GI) tract shape and volume from magnetic resonance imaging (MRI) scans.
* The successful candidate will have a strong background in deep learning for image analysis, particularly image segmentation, and experience working with large 3D datasets such as MRI scans or microCT scans.
* A Ph.D. in Developmental Biology, Cell Biology, Computational Biology or a related field is required, with a strong track record of publishing papers in refereed journals.
We are looking for an ambitious and experienced computational biologist to join our team and contribute to the development of AI-based image analysis methods for the extraction of GI tract shape data from whole-body MRI scans.
About the Role:
The Miguel-Aliaga lab is seeking to understand how organs sense and react to their environment to maintain or change physiology. To this end, they focus on the study of the intestinal tract; certain diets, microbes, or internal states can cause it to grow or shrink. Current projects explore this plasticity across scales.
Following previous work on the role that the shape of the gastrointestinal (GI) tract plays in health and disease in the fruit fly, we are now working on extending this work into analysis of human GI tract shape. We have adapted our methods to analyze GI tract shape in abdominal MRI scans and now wish to scale this up to a larger dataset.
About You:
To succeed in this role, you will need:
* A Ph.D. in a relevant field, preferably with expertise in deep learning for image analysis and experience working with large 3D datasets.
* A strong track record of publishing papers in refereed journals, with evidence of presenting research at scientific meetings.
* Experience with languages such as R and Python for image analysis and familiarity with ImageJ/FIJI.
We offer a dynamic and collaborative environment, with opportunities for professional growth and development. If you are passionate about computational biology and image analysis, and want to make a meaningful contribution to our research, please apply.