Join the Computational Clinical Psychology Lab and contribute to cutting-edge research on emotional disorders and affect science! The focus of the lab is using innovative statistical and machine learning strategies to improve the treatment and classification of emotional disorders (i.e., anxiety and depression disorders). Specifically, the principal objective of the lab’s research is to improve diagnosis, prevention, and treatment of emotional disorders by embracing a precision medicine framework that uses computational modelling to capture the idiographic, dynamic, and multidimensional nature of emotional disorders. Our research emphasizes time-series methods and intensive longitudinal data such as ecological momentary assessment (EMA) of affect and digital passive sensor data. Many of the statistical techniques emphasized in the lab span disciplines such as network theory, dynamical systems, and machine learning, among others.
Research staff receive mentorship in assisting in all aspects of computational clinical research on emotional disorders, making it an excellent fit for individuals considering graduate school in clinical or counseling psychology with a quantitative focus. This position typically involves assisting in the management of lab infrastructure and datasets, conducting research activities (e.g., IRB writing, data management, statistical analysis, etc.), supporting lab members in developing and running clinical psychology experiments and EMA research, as well as manuscript and grant preparation. Research staff will gain invaluable experience in advanced quantitative methods, time-series data, and pursing independent research on emotional disorders.
Research staff typically hold a Bachelor’s or Master’s degree in Psychology, Statistics, or a related discipline. A strong attention to detail, exceptional organizational skills, and a passion for learning statistical methods are desirable qualities in research staff. Successful individuals are also self-motivated, efficient, and able to work independently. Although programming experience (e.g., R or Python) could be helpful, it is certainly not a requirement for this position.
Postdoctoral researchers receive mentored experience in conducting independent and collaborative research projects. A central component of this position is the provision of career development guidance to facilitate academic independence and successfully navigate future academic careers. Postdoctoral research is based on mutual interests, with a broad emphasis on applying advanced statistical or computational methods (e.g., machine learning, dynamic time-series analyses, etc.) to better our understanding of emotional disorders and develop better precision medicine treatments.
Postdoctoral researchers with existing technical and quantitative psychology experience and the desire to lead projects related to the aforementioned topics will represent a strong fit. Postdoctoral researchers typically hold a PhD in Psychology, Statistics, or a related field with demonstrated experience leading research relating to the above topics.
Graduate students receive mentored experience in computational clinical psychology related to the aforementioned topics. Training will emphasize the development of both clinical and research skills in pursuing clinical research on emotional disorders. Clinical training will involve learning how to provide empirically supported assessments and treatments for anxiety and depression (e.g., cognitive behavioral therapy, mindfulness, etc.). Research training will involve acquiring competencies in advanced statistics and conducting time-series and treatment research.
If you are interested in discussing potential opportunities, please feel free to reach out and email me at j.curtiss<at>northeastern.edu