Andrei Irimia
professor
Research Interests
Explore related searches
Contact this professor
Get a free first email built on one of their papers, ready for you to edit and send yourself.
Positions (1)
Andrei Irimia
University of Southern California
Andrei Irimia at the University of Southern California is recruiting postdoctoral fellows for research at the intersection of artificial intelligence, machine learning, neuroimaging, brain aging, neurodegenerative disease, imaging genetics, spatial transcriptomics, and computational neuroscience . The lab develops next-generation AI methods for understanding the human brain by combining machine learning with large-scale neuroimaging, genetics, and transcriptomics. Current research directions include AI for neuroimaging, interpretable and explainable deep learning, multimodal biomarker discovery, polygenic risk, and precision neuroscience. The group works with major datasets such as UK Biobank, ADNI, NACC, HCP, and TRACK-TBI, plus unique multimodal MRI/genomics/transcriptomics resources. This is a strong fit for candidates with backgrounds in computer science, neuroscience, biomedical engineering, statistics, applied mathematics, physics , or related quantitative fields. Ideal applicants should have a strong publication record, excellent Python/deep learning programming skills, and experience in machine learning, medical imaging, computational biology, or related areas. The position is supported by multiple active NIH grants and offers substantial scientific independence, opportunities to initiate original projects, interdisciplinary collaboration across USC and beyond, and mentorship aimed at launching independent careers in academia or industry. To apply, email a CV, a brief statement of research interests and career goals, and up to three representative publications or preprints to [email protected] . No deadline is stated in the post.
Articles (12)
Year:
2024
Year:
2024
Year:
2023
Brain regions’ rates of age-related volumetric change after traumatic brain injury (TBI) are unknown. Here, we quantify these rates cross-sectionally in 113 persons with recent mild TBI (mTBI), whom we compare against 3 418 healthy controls (HCs). Regional gray matter (GM) volumes were extracted from magnetic resonance images. Linear regression yielded regional brain ages and the annualized average rates of regional GM volume loss. These results were compared across groups after accounting for sex and intracranial volume. In HCs, the steepest rates of volume loss were recorded in the nucleus accumbens, amygdala, and lateral orbital sulcus. In mTBI, approximately 80% of GM structures had significantly steeper rates of annual volume loss than in HCs. The largest group differences involved the short gyri of the insula and both the long gyrus and central sulcus of the insula. No significant sex differences were found in the mTBI group, regional brain ages being the oldest in prefrontal and temporal structures. Thus, mTBI involves significantly steeper regional GM loss rates than in HCs, reflecting older-than-expected regional brain ages.
Year:
2023
Year:
2023
Year:
2022
Year:
2022
Year:
2022
Year:
2022
Year:
2021
Year:
2021
Year:
2021
Collaborators (11)
Hamed Akhlaghi
Head of Emergency Research, Emergency Physician
St. Vincent's University Hospital
Emily Dennis
University of Utah
Adam Clemente
Lecturer (Psychology)
Australian Catholic University
Richard M Leahy
University of Southern California
Peter Wilson
Professor of Developmental Psychology, Healthy Brain & Mind Research Centre (HBMRC)
Australian Catholic University
Nicholas Davenport
University of Minnesota
Anand Joshi
University of Southern California
Seth Disner
University of Minnesota
Jeremy Elman
Assistant Professor
University of California San Diego School of Medicine
Govinda Poudel
Senior Lecturer
Australian Catholic University
Karen Caeyenberghs
Deakin University
Make your next move.
Prepare your application
Review drafts before you send them.