The Nielson Lab in the Department of Psychiatry & Behavioral Sciences at the University of Minnesota is seeking a Post-doctoral Associate to join the lab working in the exciting new field of computational psychiatry research for trauma. The position will involve multidisciplinary research projects in the fields of psychiatry, neurotrauma, biomedical informatics and data science. The project is funded by an R01 from the National Institutes of Mental Health.
Construct datasets from various data sources for mental health and neuropsychiatric disorders, including longitudinal psychometrics, diagnostic measures, biospecimen assays, treatments, imaging and physiology data.
Design and implement data infrastructure; ensure the integrity and security of data, code, and analytical experiments that are HIPAA compliant.
Design, setup and run computational experiments to evaluate and benchmark cutting-edge machine learning algorithms.
Develop and/or implement data-mining, statistical, machine learning, bioinformatics/clinical informatics algorithms on various types of mental health and neuropsychiatric disorders data.
Create documentation for all software, code and experiments.
Write or help prepare publications, grants, protocols and technical reports.
Communicate and present analytical results to other scientists and clinicians at seminars and conferences.
Doctoral degree (e.g. PhD, PsyD, MD, etc.) in biological sciences, neuroscience, psychology, or related field
Experience with basic machine learning or statistical methods.
Experience publishing scientific papers in conferences/journals
Experience with Matlab or Python or R.
Experience working with messy real-world data
Demonstrated/documented strong communication skills
Experience publishing within neuroscience, psychology, psychiatric journals
Experience in high-performance computing
Experience working independently in a rapidly changing scientific environment
Skills in data visualization
Experience with SQL or other database technology
Experience writing code for complex computer programs independently. Please provide a link to samples of your code available online (Github or similar services).
Internal Number: 326802
About Nielson Lab at the University of Minnesota
The overarching purpose of the Nielson lab is to understand and treat trauma. Research projects in the Nielson lab utilize a multidisciplinary approach, merging the fields of neurobiology, psychiatry and informatics to identify more precise "bio-types" of trauma psychopathology than traditional diagnostic criteria, and potential novel targets for treatment. We use established and emerging machine learning methods with multi-modal data spanning across a diverse range of diagnostic categories for neuropsychiatric disorders. Our approach is part of the rapidly growing field of computational psychiatry, where mental health data can be used to run hypotheses on in silico models to understand the complexity involved in these disorders. An advantage of such approaches is the minimization for the need to test hypotheses in animal models (in vivo). Dr. Nielson received an Early Stage Investigator (ESI) award from NIMH to apply these methods to large datasets from trauma-exposed patients to identify and validate dimensions of post-traumatic stress (PTS), relevant biological predictors, and precision treatment response trajectories.