A deeper understanding of human cognition and mental health through AI and Data Science

Research project description

PhD will investigate our understanding of human cognition and affective experience in health and disease through the lens of predictive processing, particularly in the field of emotion, social perception, and creativity, which are heavily related to mental health. Utilizing AI and data science, we aim to provide deeper analyses and novel methodologies, bridging cognitive science and technology for mental health research. 

Research Goals: 

• AI-Driven Analysis of Behavioral Data: Using a comprehensive behavioral database from healthy individuals and individuals with different mental-health related conditions, the project employs AI algorithms to explore patterns of predictive processing and their relation to psychological well-being. This involves data exploration, machine learning, model development, and hypothesis testing in cognitive science. 
• Innovative Study of Creativity and Mental Health: AI-Powered Creativity Assessment: Developing an AI platform for scenario-based prompts to measure human creativity. 
• NLP Techniques in Creativity Analysis: Applying NLP methods to evaluate the originality and depth of creative responses, combining cognitive science and computational linguistics. 
• Exploring Creativity-Mental Health Links: Investigating the connections between creativity metrics and mental health conditions to uncover new insights into cognitive foundations. 

Impact: This project proposes a transformative approach to mental health research by integrating AI and data science. It offers a multidimensional and transdiagnostic understanding of mental health, providing an exceptional opportunity for computer scientists to apply and advance AI and data science in a pioneering field. The expertise gained will be valuable in academic and industry settings, opening diverse career paths in technology, healthcare, and more. 

Academic background / Skills

Candidates must hold a degree that allows admission to the official doctoral programme at UAB.  

Additional requirements for a stronger application are: 

• Master’s degree in Data Science, Mathematics, AI, or Computer Science. 
• Background in Mental Health, Medicine, or Psychology is a plus. 

Preferred Skills and Learning Opportunities: 

• Coding abilities, especially in languages relevant to data analysis and AI, like Python and R. 
• Experience with machine learning frameworks like Scikit-learn, PyTorch, or Keras is highly valued. 
• Familiarity with NLP techniques and tools. Experience in fine-tuning and applying Large Language Models, such as ChatGPT or LLAMA, is highly valued. 
• Competence in handling, analyzing, and visualizing large datasets. 
• A foundation in probability and statistics is helpful for data analysis and AI modeling. 
• Collaborative team spirit. 
• Understanding of ethical standards in AI research, with particular attention to handling confidential health-related data. 

Research group/s description

The present PhD project is a truly transdisciplinary proposal involving two groups of research: 

1) The AI and Data Science Research Group is a multidisciplinary team of experts at the Computer Vision Center (UAB) and the University of Barcelona united to harness tech for societal benefit. The team includes specialists in artificial intelligence, machine learning, data analysis, and mental health. They specialize in creating AI solutions for predictive tasks, text analysis, and tailored treatment approaches, seeking to enhance mental health care using AI- driven methods. 

2) The Cognitive and Affective Science Laboratory, led by Lorena Chanes, is a research group at the Department of Clinical and Health Psychology-Institute of Neurosciences. Their research focuses on cognitive and affective processes that ultimately lead to conscious experience and how they relate to mental health. They have a multidisciplinary approach including behavior, non-invasive brain stimulation and neuroimaging.