PhD Position in Computational Neuroscience | University of South Carolina

Institution: University of South Carolina – Dr. Sha’s Lab, Department of Psychology

Position: PhD Student in Computational Neuroscience

Research Area: Computational Neuroscience | Neurodevelopment | Autism Spectrum Disorders | Machine Learning | Deep Learning | Neuroimaging | Brain Development | Biomedical Research

Dr. Sha’s Lab at the University of South Carolina is seeking motivated PhD students in Computational Neuroscience to investigate the mechanisms underlying atypical brain development and neurodevelopmental disorders
, including autism spectrum disorders.

The lab is affiliated with the Carolina Autism & Neurodevelopment Center, Institute for Mind & Brain, McCausland Center for Brain Imaging
, and works closely with the Center of SC Metropolitan Area
.

The research combines computational modeling, machine learning, deep learning, and neuroimaging to study neural circuitry, early-life adversity, psychopathological phenotypes, and treatment outcomes.

Apply computational modeling, machine learning, and deep-learning approaches to investigate neural circuitry and atypical brain development
.

Study mechanisms associated with neurodevelopmental disorders
, including autism spectrum disorders and related behavioral and neural phenotypes.

Analyze neuroimaging data, including MRI datasets
, to investigate brain structure, function, and neural circuitry.

Investigate how early-life adversity may influence brain development and contribute to psychopathological phenotypes.

Use computational and neuroimaging approaches to study treatment outcomes and factors associated with individual differences in response.

The PhD research will involve areas such as:

• Computational neuroscience
• Machine learning
• Deep learning
• Computational modeling
• MRI data analysis
• Early-life adversity
• Psychopathological phenotypes
• Treatment outcomes
• Biomedical research

The lab uses computational and neuroimaging approaches to understand complex relationships between brain development, behavior, and neurodevelopmental disorders
.

Potential research activities include:

• Computational modeling of neural systems.
• Development and application of machine-learning models.
• Deep-learning approaches for neuroimaging analysis.
• Analysis of MRI datasets.
• Investigation of neural circuitry.
• Study of atypical brain development.
• Analysis of autism-related neurodevelopmental patterns.
• Investigation of early-life adversity and brain development.
• Analysis of psychopathological phenotypes.
• Investigation of treatment outcomes.
• Integration of computational modeling with neuroimaging.
• Analysis of in-house and publicly available datasets.

Applicants should have a Bachelor’s or Master’s degree in a relevant field such as:

• Mathematics
• Data Science
• Biomedical Engineering
• Or another closely related field

Candidates should have:

• Strong interest in computational neuroscience.
• Quantitative and analytical skills.
• Interest in neurodevelopment and brain research.
• Familiarity with computational or data-analysis approaches.
• Interest in machine learning and/or deep learning.
• Experience with MRI data analysis is preferred.
• Coding experience is preferred.
• Background in computational modeling or data science would be relevant.

• Hands-on experience in computational neuroscience research
  .
• Training in advanced neuroimaging methods.
• Experience working with MRI and biomedical research techniques
  .
• Access to rich in-house and public datasets
  .
• Exposure to advanced 3T and 7T MRI platforms
  .
• Experience applying machine learning and deep learning to neuroscience.
• Experience with computational modeling of neural systems.
• Opportunity to study neurodevelopmental disorders and brain development.
• Training…