Students & Opportunities

Recruitment

Postdoctoral Research Fellow, Neuroimaging Genomics and Metabolomic for Aging and Alzheimer’s Disease

Interested candidates: please email a cover letter, CV, and contact information for >=3 references to Dr. Da Ma (dma@wakehealth.edu).

Applications are invited for a full-time Postdoctoral Research Fellow position affiliated with the NIA P30 Alzheimer’s Disease Research Center (ADRC) at Wake Forest University School of Medicine. The fellow will be involved in neuroimaging multi-omics (e.g. genomics, metabolomics) research with a focus on Alzheimer’s Disease through integrated data-driven approaches. The position will offer opportunities to develop advanced machine/deep learning and biomedical informatics solutions to analyze large-scale multi-dimensional neuroimaging, genomics, metabolomics, and other fluid biomarkers, as well as clinical diagnostic data. The fellow will horn experience in integrated analytical approach of multi-type information fusion strategies to understand multi-mobility pathological cascade and heterogeneity in the sub-phenotypes related to Alzheimer’s Disease and related dementia. The fellow will be responsible

Resource & Training Environment

The candidate will train under the mentorship of fellowship supervisor Dr. Da Ma, in partnership with the multidisciplinary collaborators at the Wake Forest Alzheimer’s Disease Research Center (ADRC) and Center for Biomedical Informatics. The Wake Forest ADRC has over 90 full-time faculty members whose research spans basic, clinical, and population domains. A primary focus of the Center is the role of metabolic and vascular dysregulation in AD using translational rodent and non-human primate models, and clinical research. Postdocs in the Center gain knowledge, skills, and competencies in assessing specific clinical health outcomes, the design, and conduct of observational and/or interventional studies, and technological research methodology, and are taught and encouraged to submit research proposals for grant funding. The fellow will also have the opportunity to participate in the integrated role with the Data Core, Image Core, and Biomarker Core in the ADRC.

Wake Forest is a top-50 medical school is located in Winston-Salem, NC, between the beautiful NC coast and mountains, and is known for high quality of life and low cost of living. Wake Forest School of Medicine is an affirmative action and equal opportunity employer with a strong commitment to achieving diversity among its faculty and staff.

Candidate Requirements

• Candidate should have a Ph.D. in computer science, medical image computing, Biomedical Engineering/Informatics, Biostatistics, or related quantitative fields at the time of the fellowship appointment, with a record of academic productivities. Applicants should have prior exposure to neuroscience research. Preference will be given to candidates who have prior experience and strong interest with computational analysis of integrated biomedical data, including but not limited to multi-modal neuroimaging, high throughput genomic, and another high-throughput multi-omics dataset.
• Solid background in machine learning, deep learning, medical image computing, bioinformatics, and programming skills in Python, Matlab, R, and cloud computing (SGE/Slurm Cluster, Google Cloud, Microsoft Azure) are highly desired.
• Applicants must be U.S. citizens or U.S. permanent residents, and must be interested in pursuing an academic research career. Salary commensurate with experience according to NIH levels.

Application Instructions

To apply, please email Dr. Da Ma (dma@wakehealth.edu) with a cover letter detailing your interest in this position , your most up-to-date curriculum vitae, and the contact information for 3 references. (Subject line: Neuroimaging genomics postdoctoral fellowship)

Graduate (PhD/MSc) position opportunities

I am also recruting highly motivated students to conduct research in area including:

• Computational Neuroanatomy using Graph Convolutional Network (GCN)
• Genomic-based deep learning using Natual Language Processing (NLP) models
• Multiomic analaysis explainable graph neural network to cluster and predict to age-gelated biological process mechanisms.
• Explainable AI methods to validate, understand and visualize machine learning models in medical applications to facilitate clinical translation.

Current & Previous Students

Graduate Students

• Ricky Shuo Chen (Ph.D Candidate, co-supervised with Dr. Mirza Faisal Beg)
• Donghuan Lu (Ph.D. co-supervised with Dr. Mirza Faisal Beg, Now at Tencent Jarvis Lab)
• Setarah Dabiri (Ph.D. co-supervised with Dr. Mirza Faisal Beg)
• Evangeline Yee (M.Sc., co-supervised with Dr. Mirza Faisal Beg)
• Oshin Sanga (M.Sc, co-supervised with Dr. Mirza Faisal Beg, Now at Self Care Catalysts)
• Julian Lo (M.Sc, co-supervised with Dr. Marinko Sarunic)
• Timothy Yu (M.Sc, co-supervised with Dr. Marinko Sarunic, Now at Huawei)
• Ghazal Mirab (M.Sc, co-supervised with Dr. Mirza Faisal Beg)

Undergraduate Students

• Stefan Ungurean (B.A.Sc (Honors), co-supervised with Dr. Mirza Faisal Beg, now at Amazon)
• Hanaa Diab (B.A.Sc (Honors), co-supervised with Dr. Mirza Faisal Beg)
• Cyrus Wachong (B.A.Sc (Honors), co-supervised with Dr. Marinko Sarunic)