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CHEManager International · 3 days ago

Post-Doctoral Associate

Twin Lakes, MN

Full-time

Onsite

Mid, Senior Level

$56K/yr - $62K/yr

CHEManager International is seeking a Post-Doctoral Associate to join Dr. Bayat's group at the Institute for Health Informatics at the University of Minnesota, Twin Cities. The role involves conducting research and development in medical imaging and analysis, publishing findings in peer-reviewed journals, and participating in grant writing and mentorship programs.

Newspapers

Responsibilities

Conduct research and development in medical imaging and analysis

Publish papers in peer-reviewed journals and present at technical and clinical conferences

Participate in grant writing, mentorship and career development programs

Qualification

PhD in relevant fieldMachine/deep learning algorithmsMedical imaging analysisPublications in peer-reviewed journalsHigh-performance computing (HPC)Deep learning methodsMultidisciplinary teamworkGrant writingMentorshipCommunication skills

Required

PhD in Biomedical Eng., Computer Science/Eng., Electrical Eng., Math/Statistics, Medical/Health Informatics

Strong computational and programming skills with abilities to develop cutting-edge large-scale machine/deep learning algorithms using high-performance computing (HPC)

Prior experience in medical imaging & analysis and/or computer vision algorithm development using high performance computing (HPC)

Publications in peer-reviewed technical/clinical journals or machine learning flagship conferences (CVPR, ICCV, ICLR, NeurIPS, MICCAI, etc....)

Desire to interact with multidisciplinary teams across campus, especially the IHI, Medical School and College of Science and Engineering

Preferred

Hands-on experience in developing deep learning methods for medical imaging and analysis with coursework and training in medical imaging

Experience in using general purpose medial toolkits and suites such as 3Dslicer, Open inventor, VTK, imageJ, AMIRA, etc

Knowledge of medical image data formats and routine medical image analysis tasks such as segmentation, classifications, etc

Experience in developing automated analysis methods for image reconstruction, enhancement, analysis and integration of heterogenous data with medical image informatics

Experience developing modern deep learning models such as generative models, diffusion models, vision transformers etc