Faculty Appointment in Radiology and Biomedical Imaging

Position Overview The Department of Radiology and Biomedical Imaging at the Yale School of Medicine invites applications for an Assistant Professor position in positron emission tomography (PET) imaging. Appointments are available on both the traditional and investigator tracks, and rank is dependent on the successful candidate’s qualifications. Successful candidates will be expected to teach undergraduate and graduate courses in related areas, develop an independent research program in collaboration with an interdisciplinary team of faculty, and secure external research funding. Responsibilities Development, characterization, and validation of novel imaging biomarkers with PET. Pharmacokinetic modeling of novel radiopharmaceuticals. Development of advanced image reconstruction algorithms for quantitative PET and PET/MR imaging. Development of deep learning methods to improve quantitative PET imaging. Research Environment The Yale University PET Center located on Howard Avenue in New Haven, CT is a 22,000‑sq. ft. facility that houses an advanced radiochemistry laboratory and an imaging and data analysis section. The Center collaborates with other School of Medicine departments to provide educational opportunities for doctoral and postdoctoral trainees, and with industry partners to advance the use of molecular imaging in drug discovery and PET radiopharmaceutical development. Current research interests focus on disorders of the central nervous system (CNS), oncology, cardiology, and diabetes. Qualifications Ph.D. or MD/PhD in biomedical engineering, physics, electrical and computer engineering, computer science, applied mathematics, or related fields. Experience and a track record of publications in two of the following areas: PET imaging physics, modeling of PET data and corresponding physical corrections. Tomographic image reconstruction, including conventional algorithms and penalized reconstruction techniques. Radiotracer development, experimental data acquisition (arterial blood, plasma, radiometabolite analysis using HPLC), pharmacokinetic modeling (blood-based and reference region models), and use of numerical solvers for model fitting. Deep learning tools and methods for image denoising, reconstruction, segmentation, and classification. Technical Skills Experience with computer science and data science, image processing and analysis. Proficiency with programming languages such as C/C++, Python, MATLAB, R, and Linux scripting (e.g., bash). Strong verbal and written communication skills demonstrated by publication track record and experience with grant writing. Mentoring skills for undergraduate and graduate students, interns and visitors. Desired Qualifications Experience with MR imaging and MR image reconstruction and analysis. Experience with brain imaging and knowledge of biomarkers in Alzheimer’s and other neurodegenerative diseases. Familiarity with optimization theory and applications to inverse problems. #J-18808-Ljbffr Society of Nuclear Medicine and Molecular Imaging