Postdoctoral Fellow - CSEE - Statler College of Engineering and Mineral Resources

The Lane Department of Computer Science and Electrical Engineering of the Benjamin M. Statler College of Engineering and Mineral Resources at West Virginia University invites applications for a Postdoctoral Fellow position to work with researchers at the West Virginia-Arkansas Center for Research and Education in Smart Health (WVAR-CRESH). WVAR-CRESH is a key part of a recent large NSF funding to enhance collaboration between researchers in West Virginia and Arkansas on problems in healthcare. The long-term goal of the collaboration is to improve health and well-being by accelerating decision making for smart health applications, through the development and application of advanced artificial intelligence (AI) techniques, exploiting the available massive heterogeneous biomedical datasets. Activities under this collaboration will lead to improved workforce development in leading-edge technology areas of data science, AI, and smart health. For more information about WVAR-CRESH, please visit https://community.wvu.edu/~daadjeroh/projects/cresh/ .

We are searching for candidates with a strong background in computer vision, deep learning, applied mathematics, and biomedical image analysis, especially ultrasound images. The center is focused on developing new algorithms and techniques that use advances in AI and machine learning to analyze different types of biomedical data. Emphasis is on cardiovascular health (especially on the analysis of cardiac images, such as echocardiographs, MRI, CT images, etc), health disinformation, and privacy preserving health data analytics.

The Postdoctoral Fellow will conduct research on one or more of the topics above. Together with the project team members, the Postdoctoral Fellow will have the opportunity to determine the specific direction of their research project within the scope of the collaborative projects in the center, depending on their interests.

Qualifications :

The successful candidate must have a PhD in computer science, electrical engineering, computer engineering, biomedical engineering, applied mathematics, physics or a related field. Familiarity with machine learning/deep learning/data analytics is a requirement and proficiency in scientific computing using one or more of the major programming languages/environments (python, PyTorch, Matlab, C/C++, or R) is essential.

West Virginia University is the State’s comprehensive Land Grant University with an enrollment of about 29,000 students and a R1 Carnegie Classification. Morgantown and its vicinity have a diverse population of about 62,000 residents and are ranked highly among the most livable small cities in the country. The community lies within a high technology corridor that also includes several federal research facilities, as well as industries active in shale gas operations. The city is readily accessible and within driving distance from Pittsburgh, PA and Washington, DC. For more information on WVU and Morgantown, see https://www.wvu.edu and http://www.morgantownwv.gov . The Lane Department of Computer Science and Electrical Engineering has 30 faculty members and approximately 500 undergraduate and 160 graduate students.

To apply for this position, visit https://wvu.taleo.net/careersection/faculty/jobdetail.ftl?job=20993 . Applicants must submit a cover letter, curriculum vitae, and contact information for two professional references. Only applicants who submit complete documentation will be considered in the review process. For further questions or additional information, please contact Dr. Don Adjeroh via email donald.adjeroh@mail.wvu.edu or Dr. Gianfranco Doretto via email gianfranco.doretto@mail.wvu.edu .

At West Virginia University, we leverage our talents and resources to create a better future for our state and the world. As West Virginia's land-grant university, WVU has three campuses that touch each corner of the state. The WVU System includes 518 buildings on 15,880 acres, Extension Service offices in all 55 counties, ten experimental farms and four forests.

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