MSCA Postdoctoral Fellowships (PF) on “Deciphering the Brain-Heart Symphony: AI-Powered Signal Processing for Central-Autonomic Interactions”

The increasing awareness of the intricate relationship between the brain and the heart has led to a surge in interdisciplinary research exploring their interplay. This post-doctoral research project aims to investigate the functional brain-heart interplay through advanced multivariate analysis mainly of electroencephalography (EEG), intracranial EEG (iEEG), functional MRI, functional NIRS and electrocardiography (ECG) signals. The project may also capitalize on recent developments in artificial intelligence (AI) and machine learning (ML) to elucidate novel insights into the bidirectional communication between these vital organs.

Objectives:

1. Develop advanced signal processing techniques to extract meaningful features from neural and peripheral biosignals that represent the functional interplay between the brain and the heart.
2. Employ machine learning algorithms to identify and quantify complex patterns of brain-heart interaction, including the influence of cognitive, emotional, and physiological factors.
3. Investigate the underlying neural and cardiovascular mechanisms that contribute to the observed brain-heart interplay, with a focus on understanding their implications for health and disease.
4. Develop a predictive model that leverages the extracted features and patterns to assess the risk of cardiovascular and neurological disorders, as well as toinform personalized therapeutic interventions.

Methods:

The successful post-doctoral candidate will be responsible for implementing the following research methods:

1. Collection and preprocessing of high-quality EEG and ECG data from healthy participants and individuals with specific neurological and cardiovascular conditions.
2. Development and optimization of multivariate signal processing techniques, including time-frequency analysis, source localization, and connectivity analysis, to extract relevant features from the EEG and ECG data.
3. Application of advanced machine learning techniques, such as deep learning, support vector machines, and random forests, to classify and predict different states of brain-heart interaction.
4. Validation of the developed models using independent datasets and cross-validation techniques to ensure generalizability and robustness.
5. Integration of the findings into a comprehensive framework that delineates the functional brain-heart interplay and its implications for health and disease.

Expected Outcomes:

The outcomes of this project will significantly advance our understanding of the complex brain-heart interplay and provide novel insights into the neural and cardiovascular mechanisms that underlie this relationship. Moreover, the developed predictive models can potentially be used as a diagnostic tool to identify individuals at risk of developing cardiovascular and neurological disorders. Ultimately, the findings may inform the development of personalized therapeutic strategies that target both the brain and the heart to promote overall health and well-being.

This post-doctoral research position offers an exciting opportunity for a motivated and talented individual to contribute to a rapidly evolving field with significant potential for real-world impact. The successful candidate will have access to state-of-the-art facilities, as well as the opportunity to collaborate with a multidisciplinary team of experts in neuroscience, cardiology, and computational sciences.

Hosting laboratory: Neuro-Cardiovascular Intelligence Lab of the University of Pisa (Italy)

                                   http://ncil.ing.unipi.it

Supervisor: Prof. Gaetano Valenza (http://www.centropiaggio.unipi.it/~valenza)

Eligibility criteria

Applicants must have a PhD degree at the time of the deadline for applications (11^th September 2024). Applicants who have successfully defended their doctoral thesis but who have not yet formally been awarded the doctoral degree will also be considered eligible to apply.

At the call deadline, the applicant must have a maximum of 8 years experience in research, from the date of the award of their PhD degree. Years of experience outside research and career breaks will not count towards the above maximum, nor will years of experience in research in third countries, for nationals or long-term residents of EU Member States or Horizon Europe Associated Countries who wish to reintegrate to Europe.

Mobility Rule: The applicant may be of any nationality but must not have resided or carried out their main activity (work, studies, etc.) in Italy (for European Fellowships) or the host organisation for the outgoing phase (in case of Global Fellowship) for more than 12 months in the 3 years immediately before 11^th September 2024.

Application procedure

Expressions of interest must be sent by email to GAETANO.VALENZA@UNIPI.IT no later than MAY 31, 2024  and must consist of two pdf files:

1. Complete and updated CV, clearly demonstrating all 3 eligibility requirements.
2. Motivation letter, maximum one page.