Deadline for application: 24 April 2025 at 1:00 p.m. CEST.

Selection announcement

Modello CV [italiano]

CV Template [English]

Decree of Acts Approval and Ranking

The post Bando di selezione PNC2025-01 per il conferimento di n. 1 borsa di ricerca appeared first on PNC.

Deadline for application: 18 December 2024 at 1:00 p.m. CET.

Selection announcement

Modello CV [italiano]

CV Template [English]

Decree of Acts Approval and Ranking

The post Bando di selezione PNC2024-04 per il conferimento di n. 1 borsa di ricerca appeared first on PNC.

“Aggregazione e armonizzazione di dati retrospettivi e prospettici di neuroimmagini, clinici e comportamentali relativi a ictus, glioma e malattia di Parkinson” (in English: “Aggregate and harmonise retrospective and prospective neuroimaging, clinical and behavioural stroke, glioma and Parkinson’s data”), Research Supervisor Prof. Maurizio Corbetta

Purpose of the Research Grant

The purpose of this Research Grant, which is funded by the European Union in the framework of the Horizon Europe project “EBRAINS 2.0: A Research Infrastructure to Advance Neuroscience and Brain Health”, Principal Investigator Prof. Maurizio Corbetta, is to grant research into:

The EBRAINS project (European Brain Research Infrastructures, https://www.ebrains.eu/) is an innovative collaborative research infrastructure created with the aim of advancing and accelerating scientific progress in the field of neuroscience and Brain Health. This innovative platform, derived from the Human Brain Project (HBP), is an ecosystem in which researchers, clinicians, and experts from various disciplines converge to explore and analyse the complexity of the brain at various scales, from the molecular and cellular level to whole organ functioning and the implications on human behaviour and disease. The ambition of EBRAINS is to create a new standard for brain atlases from the micro- to the macro-scale, integrating clinical, demographic and brain connectivity data (connectomes) from healthy and pathological brains; to create digital twin brains through mathematical models enabling simulations of the effects of pathologies or brain stimulation; to serve as a preferred and competitive infrastructure for the use of neuroscience data according to FAIR (Findable, Accessible, Interoperable, Re-usable) principles.

Activity: The research fellow will play a pivotal role in aggregating and harmonizing extensive retrospective and prospective collections of neuroimaging, clinical, and behavioural data related to brain pathologies such as stroke, glioma, epilepsy, and Parkinson’s disease. S/He will systematically collect and integrate data from multiple centers around Europe, ensuring consistency and compatibility across diverse datasets. Responsibilities include initiating and coordinating prospective data collection using standardized protocols, conducting data cleaning and normalization, and developing workflows for the extraction and public release of imaging features from clinical datasets. The research fellow will process clinical neuroimaging data (structural MRI, DWI, fMRI) ensuring data anonymity and compliance with ethical guidelines. S/He will integrate processed imaging features into the EBRAINS platform, contributing to a centralized repository that fosters collaboration and accelerates advancements in neuroscience and clinical research. Eventually, the research fellow will help in the development and validation of predictive frameworks for clinical and behavioural outcomes. Close collaboration with neurologists, neuroscientists, data scientists, and other collaborators within the consortium is essential, as well as active participation in project meetings and contributing to the development of standardized EU consensus protocols for imaging and clinical assessments.

Profile: The ideal candidate has a background in neuroscience, or a related field. S/He has experience in neuroimaging data analysis, particularly with clinical datasets involving structural MRI, fMRI, DWI and is proficient in data integration and harmonization techniques for large-scale, multi-center datasets. Strong programming and scripting skills (Python, MATLAB, Bash) are highly desirable, along with knowledge of advanced analytical techniques such as machine learning, multivariate analysis, and statistical modeling. The candidate should be familiar with processing and analyzing clinical, and behavioral data related to neurological conditions and have experience in developing workflows and pipelines for data processing and feature extraction. Excellent communication skills, both written and verbal, are required, as well as the ability to work collaboratively in a multidisciplinary research environment.

Deadline for submitting applications

3 December 2024 at 1:00 pm CET

Selection Notice

Guidelines for Submitting Applications

Decree of Acts Approval and Ranking

The post Selection notice no 4 for the awarding of one position at the Padova Neuroscience Center in the framework of the Horizon Europe project “EBRAINS 2.0 appeared first on PNC.

“Analisi multimodale della connettività cerebrale e modelli predittivi del comportamento basati su machine learning” (in English: “Multimodal analysis of brain connectivity and predictive modelling of behavior based on machine learning”), Research Supervisor Prof. Marco Zorzi

Purpose of the Research Grant

The purpose of this Research Grant, which is funded by the European Union – NextGenerationEU – through MUR PNRR fundings in the framework of the project MNESYS “A multiscale integrated approach to the study of the nervous system in health and disease” – PE00000006, Missione 4 “Istruzione e ricerca”, Componente 2 “Dalla ricerca all’impresa”, Investimento 1.3 “Creazione di Partenariati Estesi alle università, centri di ricerca, alle aziende per il finanziamento di progetti di ricerca di base”, M4C2 Spoke 2, CUP: B83C22004960002, is to grant research into:

The aim of the research fellowship is to develop analytical methods that integrate multimodal neuroimaging data at the connectome level and then derive predictions on behavior and cognition.

Activity: The research fellow will work with and contribute to the acquisition of new multimodal data (MRI, fMRI, EEG) pre-processed from healthy subjects and neurological patients. The research fellow will (i) develop an automated procedure to pre-process and analyze data from different sources in a common reference space; (ii) compare brain connectivity derived by different modalities or methods (e.g. functional vs. effective connectivity) and assess its predictivity on behavior and cognition using also machine learning methods; (iii) evaluate methods and possible benefits of integrating multimodal data.

Profile: The ideal candidate should have: (a) experience in analyzing functional magnetic resonance imaging data; (b) experience in using machine learning on neuroimaging data; (c) advanced data analysis and programming skills in Python/Matlab.

Deadline for submitting applications

1 October 2024 at 1:00 pm CEST

Selection Notice

Guidelines for Submitting Applications

Decree of Acts Approval and Ranking

The post Selection notice no 4 for the awarding of one position at the Padova Neuroscience Center in the framework of the PNRR Cascading Grant Project INSIGHTS appeared first on PNC.

“Modellizzazione multimodale dell’attività cerebrale con reti neurali ricorrenti” (in English: Multimodal modeling of brain activity with recurrent neural networks”), Research Supervisor Prof. Samir Simon Suweis

Purpose of the Research Grant

The purpose of this Research Grant, which is funded by the European Union – NextGenerationEU – through MUR PNRR fundings in the framework of the project MNESYS “A multiscale integrated approach to the study of the nervous system in health and disease” – PE00000006, Missione 4 “Istruzione e ricerca”, Componente 2 “Dalla ricerca all’impresa”, Investimento 1.3 “Creazione di Partenariati Estesi alle università, centri di ricerca, alle aziende per il finanziamento di progetti di ricerca di base”, M4C2 Spoke 2, CUP: B83C22004960002, is to grant research into:

The general aim of the research fellowship is using recurrent neural networks to jointly model brain activity observed with several imaging modalities.

Activity: The research fellow will use machine learning techniques, based on recurrent neural networks, to model brain activity observed with different imaging modalities. The research fellow will (i) use numerical simulations to develop recurrent networks that can be trained with data at different spatio-temporal resolutions; (ii) use recurrent networks to model brain activity observed with different imaging modalities.

Profile: The ideal candidate should have: (a) experience in machine learning and possibly its use to model dynamic phenomena; (b) advanced data analysis and programming skills in Python/Matlab.

Deadline for submitting applications

13 September 2024 at 1:00 pm CEST

Selection Notice

Guidelines for Submitting Applications

Decree of Acts Approval and Ranking

The post Selection notice no 3 for the awarding of one position at the Padova Neuroscience Center in the framework of the PNRR Cascading Grant Project INSIGHTS appeared first on PNC.

Title of the Project

“Analisi e modellizzazione multimodale dell’attività cerebrale” (in English: “Multimodal analysis and modeling of brain activity”), Research Supervisor Prof. Samir Simon Suweis

Purpose of the Research Grant

The purpose of this Research Grant, which is funded by the European Union – NextGenerationEU – through MUR PNRR fundings in the framework of the project MNESYS “A multiscale integrated approach to the study of the nervous system in health and disease” – PE00000006, Missione 4 “Istruzione e ricerca”, Componente 2 “Dalla ricerca all’impresa”, Investimento 1.3 “Creazione di Partenariati Estesi alle università, centri di ricerca, alle aziende per il finanziamento di progetti di ricerca di base”, M4C2 Spoke 2, CUP: B83C22004960002, is to grant research into:

The global aim of the research fellowship is developing data analysis and modeling strategies to integrate multimodal neuroimaging data within a common framework.

Activity: The research fellow will work with pre-processed multimodal data (MRI,fMRI,(i)EEG) from healthy subjects and neurological patients, and will contribute to the acquisition of new multimodal data. The research fellow will (i) develop an automatic procedure to pre-process and analyse data from different sources in a common reference space; (ii) develop a procedure to estimate and compare functional connectivity (FC) obtained with different functional data; (iii) train whole-brain models, in particular to consistently reproduce essential features of multimodal data (e.g. FC).

Profile: The ideal candidate should have: (a) experience in analysing brain activity data; (b) experience in modelling brain activity; (c) advanced data analysis and programming skills in Python/Matlab.

Deadline for submitting applications

13 September 2024 at 1:00 pm CEST

Selection Notice

Guidelines for Submitting Applications

Decree of Acts Approval and Ranking

The post Selection notice no 1 for the awarding of one position at the Padova Neuroscience Center in the framework of the PNRR Cascading Grant Project INSIGHTS appeared first on PNC.

“Modellizzazione multimodale dell’attività cerebrale e studio della risposta a stimolazioni” (in English: “Multimodal modeling of brain activity and study of the response to stimulation”), Research Supervisor Dr. Michele Allegra

Purpose of the Research Grant

The purpose of this Research Grant, which is funded by the European Union – NextGenerationEU – through MUR PNRR fundings in the framework of the project MNESYS “A multiscale integrated approach to the study of the nervous system in health and disease” – PE00000006, Missione 4 “Istruzione e ricerca”, Componente 2 “Dalla ricerca all’impresa”, Investimento 1.3 “Creazione di Partenariati Estesi alle università, centri di ricerca, alle aziende per il finanziamento di progetti di ricerca di base”, M4C2 Spoke 2, CUP: B83C22004960002, is to grant research into:

The global aim of the research fellowship is pairing whole-brain models of neural activity, trained on multimodal data, with control and perturbation theory techniques, to determine the effect of electromagnetic stimuli on brain activity, and identify the optimal stimulation loci to obtain desired effects.

Activity: The research fellow will investigate the possibility of using whole-brain models, trained on multimodal data acquired at rest, to predict the effect of electromagnetic stimulations on neuronal activity: (i) starting from the model and exploiting numerical simulations and/or perturbation theory techniques, the research fellow will develop quantitative predictions about the local and remote effect of stimulations; (ii) the predictions will be compared with the results actually measured in subjects subjected to stimulation; (iii) using control theory techniques, the research fellow will determine the optimal stimulation points to excite/inhibit the activity of specific cortical/subcortical areas and networks.

Profile: The ideal candidate should have: (a) experience in modeling brain activity; (b) experience in using models to predict the effect of perturbations; (c) advanced programming skills in Python/Matlab.

Deadline for submitting applications

13 September 2024 at 1:00 pm CEST

Selection Notice

Guidelines for Submitting Applications

Decree of Acts Approval and Ranking

The post Selection notice no 2 for the awarding of one position at the Padova Neuroscience Center in the framework of the PNRR Cascading Grant Project INSIGHTS appeared first on PNC.

“Generazione di Atlanti Normativi da Dati Multicentrici e Multimodali Acquisiti in Soggetti Sani” (in English: “Generation of Normative Atlases from Multicentric and Multimodal Data Acquired in Healthy Subjects”), Research Supervisor Prof. Alessandra Bertoldo

Purpose of the Research Grant

The purpose of this Research Grant, which is funded by the European Union in the framework of the Horizon Europe project “EBRAINS 2.0: A Research Infrastructure to Advance Neuroscience and Brain Health”, Principal Investigator Prof. Maurizio Corbetta, is to grant research into:

The project involves the generation of foundational normative atlas by acquiring advanced imaging data from a large, diverse multicentric healthy cohort. The dataset will include structural MRI, resting state fMRI, multi-shell DWI, high-density EEG, and dynamic 18F-FDG PET, providing comprehensive insights into brain anatomy, functional connectivity, white matter fiber orientations, neural electrical activity, and glucose metabolism. The acquired data will be employed to extract relevant imaging features, covering structural, functional, connectivity, activity, and metabolic aspects of the brain. Three main extraction approaches will be used: voxel-based, region-based, and connectivity-based features. Rigorous validation and quality assurance procedures will ensure the accuracy and reliability of the features. Once validated, the curated imaging features will be made available on an open-access platform to promote collaboration and advance understanding of brain function and neurological disorders.

Activity: The research fellow will share responsibilities with other researchers hired in Padua for the same EU project, including the acquisition, anonymization, pre-processing, processing, and integration of neuroimaging and simultaneously acquired HD-EEG signals on the Biograph mMR Siemens hybrid system. They will also take care of cognitive tests and clinical characteristics as part of their shared activities. The research fellow will collaborate on the voxel-level quantification of parameters from dynamic PET images obtained with [18F]FDG and on the parameters of diffusion models at both the single-subject and group levels. Additionally, they will actively collaborate closely with external collaborators, including neurologists, neuroscientists, and physicists.

Profile: The ideal candidate should have a basic experience in neuroimaging analysis and, preferably, training in bioengineering and/or applied mathematics/physics and related fields. They must have knowledge of basic and advanced analysis techniques used in neuroscience (e.g., multivariate approaches, machine learning, graph theory, etc.). Analytical/mathematical skills are required. Programming and scripting skills (Python, Matlab, Bash) are not mandatory but are a clear advantage. Furthermore, the candidate must be highly motivated and creative, with the ability to work in a dynamic and multidisciplinary research environment and be willing to interact with both experimental and theoretical neuroscientists.

Deadline for submitting applications

2 August 2024 at 1:00 pm CEST

Selection Notice

Guidelines for Submitting Applications

Decree of Acts Approval and Ranking

The post Selection notice no 2 for the awarding of one position at the Padova Neuroscience Center in the framework of the Horizon Europe project “EBRAINS 2.0 appeared first on PNC.

“Acquisizione e analisi dei segnali EEG ad alta densità per quantificare la connettività funzionale intrinseca del cervello e la sua integrazione in uno studio multimodale multicentrico” (in English: “Acquisition and analysis of high-density EEG signals to quantify intrinsic brain functional connectivity and its integration in a multicenter multimodal study”), Research Supervisor Prof. Alessandra Bertoldo

Purpose of the Research Grant

The purpose of this Research Grant, which is funded by the European Union in the framework of the Horizon Europe project “EBRAINS 2.0: A Research Infrastructure to Advance Neuroscience and Brain Health”, Principal Investigator Prof. Maurizio Corbetta, is to grant research into:

The project involves the generation of foundational normative atlas by acquiring advanced imaging data from a large, diverse multicentric healthy cohort. The dataset will include structural MRI, resting state fMRI, multi-shell DWI, high-density EEG, and dynamic 18F-FDG PET, providing comprehensive insights into brain anatomy, functional connectivity, white matter fiber orientations, neural electrical activity, and glucose metabolism. The acquired data will be employed to extract relevant imaging features, covering structural, functional, connectivity, activity, and metabolic aspects of the brain. Three main extraction approaches will be used: voxel-based, region-based, and connectivity-based features. Rigorous validation and quality assurance procedures will ensure the accuracy and reliability of the features. Once validated, the curated imaging features will be made available on an open-access platform to promote collaboration and advance understanding of brain function and neurological disorders.

Activity: The research fellow will share responsibilities with other researchers hired in Padua for the same EU project, including the acquisition, anonymization, pre-processing, processing, and integration of neuroimaging and simultaneously acquired HD-EEG signals on the Biograph mMR Siemens hybrid system. They will also take care of cognitive tests and clinical characteristics as part of their shared activities. Specifically, the research fellow will analyze EEG signals both at the scalp level and after reconstruction using source analysis. The analysis methods will be both in the time domain and in the frequency domain. Brain functional connectivity (FC) will be investigated in terms of coupling (non-directed FC) and causality (directed FC). Both approaches will be used, considering (but not limited to) spectral coherence, phase locking value, synergy, transfer entropy, and Granger causality. The research fellow will work actively in close interaction with external collaborators, including neurologists, neuroscientists, and physicists.

Profile: The ideal candidate should have a basic experience in EEG signal analysis and neuroimaging, and preferably a background in bioengineering and/or applied mathematics/physics and related fields. They must have experience in advanced analytical techniques (e.g., multivariate approaches, machine learning, graph theory, etc.). Analytical/mathematical skills are required. Programming and scripting skills (Python, Matlab, Bash) are not mandatory but represent a clear advantage. Additionally, the candidate should be highly motivated and creative, with the ability to work in a dynamic and multidisciplinary research environment and willing to interact with both experimental and theoretical neuroscientists.

Deadline for submitting applications

2 August 2024 at 1:00 pm CEST

Selection Notice

Guidelines for Submitting Applications

Decree of Acts Approval and Ranking

The post Selection notice no 3 for the awarding of one position at the Padova Neuroscience Center in the framework of the Horizon Europe project “EBRAINS 2.0 appeared first on PNC.

“Acquisizione e analisi di un connettoma multicentrico e multimodale in soggetti sani” (in English: “Acquisition and analysis of a comprehensive multicentre and multimodal connectome in healthy controls”), Research Supervisor Prof. Alessandra Bertoldo

Purpose of the Research Grant

The purpose of this Research Grant, which is funded by the European Union in the framework of the Horizon Europe project “EBRAINS 2.0: A Research Infrastructure to Advance Neuroscience and Brain Health”, Principal Investigator Prof. Maurizio Corbetta, is to grant research into:

The project involves the generation of foundational normative atlas by acquiring advanced imaging data from a large, diverse multicentric healthy cohort. The dataset will include structural MRI, resting state fMRI, multi-shell DWI, high-density EEG, and dynamic 18F-FDG PET, providing comprehensive insights into brain anatomy, functional connectivity, white matter fiber orientations, neural electrical activity, and glucose metabolism. The acquired data will be employed to extract relevant imaging features, covering structural, functional, connectivity, activity, and metabolic aspects of the brain. Three main extraction approaches will be used: voxel-based, region-based, and connectivity-based features. Rigorous validation and quality assurance procedures will ensure the accuracy and reliability of the features. Once validated, the curated imaging features will be made available on an open-access platform to promote collaboration and advance understanding of brain function and neurological disorders.

Activity: The research fellow will share, with the other research fellows hired in Padova for the same EU project, the responsibilities for the acquisition, anonymization, pre-processing, processing, and integration of neuroimages and HD-EEG signals acquired simultaneously on the Biograph mMR Siemens hybrid system. Curation of the cognitive tests and clinical features will be also part of her/his shared activities. She/He will work and collaborate on the quantification of [18F]FDG PET as well as on the derivation of connectomics features from MR images and EEG signals. He/She will also actively collaborate in close interaction with external collaborators, including neurologists, neuroscientists, and physicists.

Profile: The ideal candidate should have experience in neuroimaging analysis and, preferable, a background in bioengineering, and/or applied mathematics/physics, and/or statistics, and/or computer science, and/or neuroscience and related fields. He/she must have demonstrated experience in advanced analytic techniques (e.g. multivariate approaches, machine learning, graph theory etc.). Strong analytical/mathematical skills are a requirement. Experience in one or more areas of neuroimaging will be plus. Programming and scripting skills (Python, Matlab, Bash) are not a prerequisite, but a clear advantage. It is required the knowledge of the following softwares: FSL, ANTs, MRtrix3, Nilearn, MNE-python, FieldTrip. Moreover, the candidate must be highly motivated and creative individual with the ability to work in a dynamic, multi-disciplinary research environment and be willing to interact with both experimental and theoretical neuroscientists.

Deadline for submitting applications

10 July April 2024 at 1:00 pm CEST

Selection Notice

Guidelines for Submitting Applications

The post Selection notice for the awarding of a position at the Padova Neuroscience Center in the framework of the Horizon Europe project “EBRAINS 2.0 appeared first on PNC.