Open Positions for Graduate Students and Postdoctoral Associate
Our laboratory at University of Illinois Urbana-Champaign has several openings for graduate students and postdocs to join Biomedical Optical Imaging Laboratory. We are advancing precision medicine through cutting-edge multiscale optical microscopy, automation and robotics, artificial intelligence (AI),
and large-scale bioimage informatics. Our imaging techniques span seven orders of magnitude—from the nanoscale to the mesoscale—enabling transformative advancements in precision medicine. Our fusion of cross-scale imaging systems, imaging probes and AI-driven bioimage informatics and systems biology is setting the stage for unprecedented scientific discoveries and transformative personalized medicine.
We have several projects at the intersection of advanced optics, cancer, artificial intelligence, and medicine, contributing to groundbreaking research with significant potential to reshape healthcare paradigms. Our open projects include optical microscopy development, automation, computational imaging, image translation and feature extraction, and various biomedical applications in predicting cancer progression risk and response to therapeutics.
Projects for Students Interested in Optics, Physics, Microscopy Instrumentation, and Automation:
- Development of automated quantitative phase microscopy for label-free imaging of 3D tissue models.
- Development of correlative label-free and super-resolution microscopy in a multi-modal imaging system.
- Development of multi-scale imaging system for ultrahigh-throughput high-content imaging.
Projects for Students Interested in Computational iImaging, Image Processing and Image Informatics:
- Development of image translation to convert label-free images to fluorescence images.
- Development of deep-learning based classification on multimodal and multiscale whole-slide images to distinguish high-risk from low-risk patients with precancers and cancers.
- Development of spatiotemproal image processing framework to extract high-dimensional information of morpho-dyhamics to predict the drug response.
- Inverse scattering problem for phase retrieval in 3D high-resolution quantitative phase imaging.
- Development of automated cell semgentation and graph neural networks for 3D spatiotemproal biology in large-scale tissue images.
Projects for Students Interested in Biomedical Applications:
- Understanding the impact of tumor microenvironment and epigenetic factors in driving precursor lesions transform into malignant tumor.
- Development of 3D high-resolution spatial profiling approaches to predict the risk of relapses in patients with inflammatory bowel diseases.
- Identifying the key epigenetic drivers in epithelial and immune cells developing resistance and biomarkers to predict patients' response to cancer theraupetics.
- 3D spatial profiling of immune adaptation in cancer progression.