Sort by
Refine Your Search
-
School. KHRI and the neuroscience community at the U-M provide a highly supportive and diverse research environment and excellent career development opportunities for postdoctoral fellows. We are committed
-
). The program is designed to provide broad exposure to an array of databases including clinical registries from the Scientific Registry of Transplant Recipients (SRTR) and United Network for Organ Sharing UNOS
-
surveys, focus groups, organizational audits, and stakeholder convenings. Coordinate data collection, management, analysis, and interpretation to inform program development and institutional recommendations
-
models (LLMs) and AI systems for hardware design. This is an exceptional platform to conduct impactful research in high-performance systems, build new networks with world-leading researchers, author high
-
models (e.g., YOLO, U-Net, EfficientNet, ResNet, FPN, Fast R-CNN) Computer vision techniques and algorithms Python and relevant libraries (e.g., PyQt, OpenCV, NumPy, scikit-learn), particularly
-
develop the cutting-edge experimental and computational approaches to accelerate natural product discovery. You will demonstrate strong teamwork, and you will have the academic freedom to independently
-
, astrophotonics and nanophotonics. The Centre offers a mentoring program for early career researchers while providing opportunities to hone other skills such as outreach, industry engagement, and building
-
nonlinear optics, quantum photonics, astrophotonics and nanophotonics. The Centre offers a mentoring program for early career researchers while providing opportunities to hone other skills such as outreach
-
one from your current graduate or clinical residency training program. Graduate-level academic transcripts (unofficial is acceptable) Two writing samples, preferably a copy of a previously published
-
technical knowledge and hands-on experience in: Deep learning frameworks (e.g., PyTorch, TensorFlow) Deep learning models (e.g., YOLO, U-Net, EfficientNet, ResNet, FPN, Fast R-CNN) Computer vision techniques