NEW! We are currently looking for strong and motivated students (and/or Fully Remote Interns as part of our Student Enrichment Opportunities) for a variety of biomedical data science projects. The partial list of current project topics and keywords are given below. Please email at firstname.lastname@example.org with your Current CV and Research Interests. We are currently looking to fill multiple positions for various projects on AI + medical image processing. Please email with subject line "Medical Image Processing - 2023" before 31st March 2023. We also have multiple internships available via an Indo-US collaborative initiative. Please email with subject line "Intern Position - 2023".
Topics & Keywords:
Image processing for various bio + medical imaging modalities with machine learning (ML) and deep learning (DL)
Biological image processing and analysis - denoising/deblurring/super-resolution/reconstructions/detection/segmentation/tracking - cells, membranes, tissues - multiplex data, multichannel data, high throughput microscopy, Cryo-EM, µCT, IHC, ISH, confocal, fluorescence, mass spec.
Medical signal/image processing and analysis - denoising/deblurring/super resolution/reconstructions/segmentation/classification - radiological imaging, Magnetic Resonance Imaging (MRI), Ultrasound, Computed Tomography, DEXA, PET/SPECT, Histology, DwMRI, fMRI, ECG, EEG.
AI models - CNN/GAN/LSTM/RNN/VAE/Transformers/Diffusion Models applied to biomedical informatics
Applications of AI models for bio + medical image processing
DL for video analysis/gait analysis/activity tracking
CNN/GAN/Transformer for scRNAseq, ATAC-seq, computational biology problems
ML/DL based QC of single cell data - Solving open problems in single-cell analysis
Multi-modal integration (imaging+non-imaging) - latent representations - fusion (early/intermediate/late) techniques
DL for electronic health records (EHRs)/clinical/health Informatics/longitudinal clinical data - natural language processing (NLP) + associated imaging Data
Bringing different applied data science tools and knowledge applied to biomedical informatics
Sparse representations for imaging data
Topological data analysis (TDA) for biomedical imaging and text data
Learning with limited/noisy-labels
Postdoctoral/Research Fellow Positions
The Prasath Lab is looking for qualified postdoctoral candidates and research fellows. Potential applicants can inquire with Dr. Prasath. The applicant will be expected to provide a current CV, a brief research statement describing past work and current interests, and the contact details of three references. Previous experience with image processing, computer vision, and machine/deep learning is preferable. Please email with subject line "Postdoc Position Application". We also work closely with a lot of other labs at CCHMC and UC, so please reach out to us to get connected to these great opportunities at CCHMC.
Graduate Student Positions - MS/MEng/PhD
Current/incoming University of Cincinnati (UC) Graduate students (regardless of the discipline of study) interested in rotating (typically 2-3 months - mix of remote/in-person) or joining the lab should arrange a Zoom/Teams meeting with Dr. Prasath to discuss possible projects of interest. Outside (international) graduate students interested in joining the lab please email Dr. Prasath and also check University of Cincinnati Graduate Programs in Biomedical Informatics and College of Engineering and Applied Science, UC. The admission committee does a good job at sharing the applications of prospective students with relevant faculty.
Undergraduate Student Positions
Undergraduate students interested in pursuing projects in the lab should inquire with Dr. Prasath. Summer undergraduate research fellowships (SURF) are available for undergraduate students interested in our areas of research. Visit the University of Cincinnati SURF page to learn more. Our previous undergraduate research fellows have worked on cutting-edge AI for biomedical image processing problems and also have won awards at the UC annual undergraduate research forums.
High School Student Positions
High School students interested in pursuing projects in the lab should inquire with Dr. Prasath. You will be paired with Senior Graduate students to work and shadow our real-world data science projects. You will have ample opportunities to work on state-of-the-art AI models applied to biomedical informatics!
Undergraduate Research in Biomedical Informatics
Discover and explore Biomedical Informatics. Apply new methods to interesting open problems in the Pediatrics domain.
Work in collaborative teams to develop new AI/ML/DL algorithms for biomedical data - signals, image, videos, text, hone soft skills, and enhance your scientific background.
Get hands-on experience in scientific research and explore career opportunities in science, technology, engineering and mathematics (STEM) - in an interdisciplinary and applied approach.
Have NO-FEAR (New Opportunities - For Engineering and Advanced undergraduates in Research) and ARISE (AI Research In Science and Engineering)! So Apply Now!!
Check out our exciting Research Projects!
Prospective students please read the following before applying:
We are always looking for motivated and creative research associates, postdocs, graduate, undergraduate, and high-school students to join our research group. Due to our base at Cincinnati Children's, much of our research focuses on Pediatric Health: the use of AI, image processing, computer vision, machine learning with the goal of improving pediatric patient care, quality of life, and serving various other divisions - Radiology, Pathology, Microscopy Core, Neurology, Neurosurgery, Pulmonary, Health Informatics, Clinical Informatics, Emergency Medicine, Immunobiology, Human Genetics,...
As our research is intensively applied, you should expect to spend a significant amount of time coding, prototyping, and running empirical studies on real-world data. This process is quite demanding and requires patience and perseverance. However, it is also quite rewarding to design systems that are actually used by pediatricians.
As with other labs, our funding situation varies, but is always a limiting factor on the size of any research group (including ours). Your best chances to joining the lab are to take classes in Machine Learning/Deep Learning (important), Image Processing (optional), Signal Processing (optional), and Computer Vision (optional). If you have a strong background in Mathematics, learning the above subjects are not mandatory and can be learned on the job.
If you are already a student at the University of Cincinnati, please free to email (email@example.com) Dr. Prasath to introduce yourself and your research interests. Reading a couple of our recent publications will give you a leg up! If you are not yet a student at the University of Cincinnati, please go through the standard admission procedures and mention our lab as a possible destination - either at Computer Science, CEAS or at Biomedical Informatics, University of Cincinnati. The admission committee does a good job at sharing the applications of prospective students with relevant faculty.
We want you!
We welcome applications at various levels - Summer Internships, Remote Internships for High School, Undergraduate, SURF (Summer Undergraduate Research Fellowship), Graduate, and PostDoctoral Fellowships.
Are you interested in solving real-life problems?
Are you interested in image processing?
Are you interested in computer vision?
Are you interested in deep learning?
Are you bored of using lame synthetic benchmarks in AI ?
Are you fed-up with devising ML/DL/AI models to juice out 0.001% improvement over baseline on the toy MNIST, FMNIST type datasets ?
Do you want to work without traditional 9 to 5 day constraints?
Do you want to positively affect pediatric patients with data-driven insights?