Connectionists: Postdoc position in neuroimaging and deep learning -the University of Texas Health San Antonio-

[Mohamad Habes]

*The Neuroimage Analytics Laboratory (NAL) and the Biggs Institute
Neuroimaging Core (BINC) are recruiting a postdoctoral fellow in deep
learning in neuroimaging*



*-the University of Texas Health San Antonio-*





We seek a talented and highly motivated *postdoctoral fellow *to join our
multidisciplinary research team.Alzheimer's disease and other dementias are
heterogeneous conditions, which makes differentiating between them and
their subtypes very challenging. Our lab focuses on leveraging advanced
neuroimaging techniques and deep learning algorithms to better understand
brain structure and function in health and disease, particularly
Alzheimer's disease. Successful candidates will have the opportunity to
contribute to cutting-edge research projects, including but not limited to
federated learning, explainable AI, and contrastive learning in
neuroimaging, among others.



The Neuroimage Analytics Laboratory (NAL) and the Biggs Institute
Neuroimaging Core (BINC) will be your work environment. We build advanced
neuroimage analytical techniques to derive discovery. Data-driven
approaches are of particular interest in our lab, as machine learning and
machine intelligence will guide the scientist toward the finding. On a
broader goal, our tools help deliver precise diagnostics on an individual's
level and ultimately could guide treatment progress.

We are part of the Biggs Institute (https://biggsinstitute.org), which is
being established as a flagship, free-standing institute within the
University of Texas Health San Antonio (UTHSA), with the mission of
establishing an interdisciplinary, integrated program to provide
comprehensive clinical care and undertake innovative and important research
into the prevention and treatment of Alzheimer's Disease and other
neurodegenerative conditions, including vascular contributions to dementia,
Parkinson's disease, and frontotemporal dementia. It has strong
institutional and community support and will benefit from existing
resources within UTHSA, such as the Barshop Institute for Longevity and
Aging Studies, the Center for Biomedical Neuroscience, the School of
Nursing, the Cancer Center, and the Research Imaging Institute, along with
the San Antonio campus of the UT Health Houston School of Public Health.

*Responsibilities*

· Develop, test, and validate novel methods with multimodal neuroimaging
data

· Apply your validated methods to large-scale research and real-life
everyday clinical routine neuroimaging data

· Willingness to work in teams within NAL, BINC, and Biggs and with
national and international collaborators

· Communicate your research results to the larger communities through
publications in international conferences and journals

· Work with a great deal of independence in achieving research goals

*Requirements*

· A Ph.D. in Neuroscience, Artificial Intelligence, Machine Learning,
Computer Vision, or Medical Image Analytics with solid experience in deep
learning; Experience in Neuroimaging and Dementia Research is a plus.

· Experience with neuroimage analytics packages like spm, fsl, itksnap, etc.

· Great eagerness to solve scientific problems

· Strong programming skills, e.g., Python, R, C++, and Java. Experience
with Python deep learning toolboxes and high-performance computational
facilities could be a plus;

· Excellent record of publishing in relevant, high-quality journals in the
above fields

· Excellent communication abilities in English, spoken and written.

To apply, please send to Dr. Habes (habes at uthscsa.edu) the following
materials to

·      A cover letter outlining your research interests, qualifications,
and career goals

·      A current CV, including contact information for at least two
references

·      Copies of relevant academic transcripts (unofficial copies are
acceptable)

·      A sample of your previous research work (e.g., a published article,
conference paper, or thesis)

Review of applications will begin immediately and continue until the
position is filled. For more information about our lab and ongoing
projects, please visit www.nallab.or.g. <http://www.nallab.org/> We thank
all applicants for their interest; however, only those selected for an
interview will be contacted.

Our institution is an equal opportunity employer and encourages
applications from all qualified individuals, including women, members of
visible minorities, Indigenous persons, and persons with disabilities.
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