2026 Topic-Specific Grants and Descriptions

This project stems from a collaboration between CIMeC (M.Piazza) and NeuroSpin, France (E.Eger, S.Viganò), and it is funded by a VINCI grant from the "Università Italo Francese". The candidate is therefore expected to spend at least 6 months at NeuroSpin. The main aim of the project is to investigate how the human brain represents music by combining behavioural experiments with high-resolution neuroimaging. Understanding how the brain represents knowledge is a central challenge in cognitive neuroscience. Recent studies have shown that the hippocampal–entorhinal–parietal system, traditionally associated with spatial navigation, also supports the organization of conceptual information into low-dimensional cognitive maps. However, many of these studies have focused on artificial stimuli or simplified experimental constructs, leaving open the question of whether the same neural principles apply to culturally acquired, complex, and highly structured knowledge systems. The project proposes musical tonality as a model system to address this question. Although music is fundamentally an auditory phenomenon, its organization has historically been described in spatial terms—from the musical staff to the circle of fifths and hierarchical models of tonal organization—suggesting a deep correspondence between musical cognition and spatial representation. The project translates this insight into neurobiological terms by asking whether the neural mechanisms that support navigation in physical space are also engaged in musical perception. Combining psychophysics and ultra-high-filed MRI (7T or 11.7T), the project tests the hypothesis that tonal representations are organized across multiple representational spaces of increasing abstraction—scale degrees, chords, and harmonic functions—and that these maps are distributed along anatomical gradients in the brain. 

The candidates should have a background in cognitive science / neuroscience as well as a strong musical background (preferably a diploma in composition). Please do get in touch with the PI for further details (manuela.piazza@unitn.it).

Neuromodulators such as acetylcholine, noradrenaline and other chemical signalling systems play a fundamental role in regulating brain function, yet we still have only a limited understanding of how they reorganize large-scale brain networks. This PhD project aims to uncover how changes in brain chemistry influence communication across the entire brain, helping explain how internal brain states shape perception, cognition and behaviour. The successful candidate will join an interdisciplinary team developing new approaches to study brain-wide activity in the mouse brain by combining cutting-edge functional neuroimaging, optical imaging and quantitative data analysis. The project offers a unique opportunity to investigate one of the central questions in systems neuroscience: how neurochemical signals orchestrate the dynamic activity of distributed brain networks in health and disease.  

Contact alessandro.gozzi@iit.it

Adaptive behaviour (e.g., in traffic or sports) requires our brain to continuously predict unfolding external events. Contemporary theories posit that our brain combines an internal model of the spatio-temporal structure of our world with new sensory input to continuously generate those predictions (e.g., [1,2,3]). However, while prediction theories of brain function are gaining traction, empirical support mostly comes from highly controlled artificial paradigms that use simple, discrete and often static stimuli. These conventional paradigms show that the brain can predict, but not that this is its normal modus operandi, thus leaving critical ambiguities as to what our brain represents at any given moment in daily life.

We recently developed a new approach in the lab that combines MEG recordings of participants observing naturalistic dynamic input (e.g., movies), with dynamic representational similarity analysis (dRSA) to quantify both the strength and the millisecond-precision latency of neural representations of naturalistic dynamic input, across hierarchical levels of stimulus complexity (from perceptual-to-conceptual). See [4,5] for relevant previous research from the lab. This fully-funded PhD position is part of a larger 5-year project funded by the Italian government (FIS starting grant) on which several PhD/postdocs will work. Depending on background and interest, the PhD student will focus on one of four research lines that all investigate how fundamental real-life factors determine the (predictive) representational dynamics of our brain under naturalistic conditions, and that are difficult to investigate with more controlled conventional paradigms. Specifically: 1) the hierarchical nature of the world, 2) its multimodal (e.g., audiovisual) nature), 3) the fact that real-world cognition is embodied/active, and 4) the interaction with naturalistic attentional orienting in the world. 

The ideal candidate should have a background in cognitive neuroscience and neuroimaging (preferably M/EEG or fMRI/fNIRS, and MVPA/RSA) and strong programming skills (preferably Matlab or Python), or have affinity for such approaches. Candidates with a neighbouring background with strong computational skills (computer science/engineering, math, etc.) are also encouraged to apply. Research line 3 includes virtual reality (VR) experiments, so for this project experience with VR (ideally combined with EEG or OPM-MEG) is a plus. Candidates are encouraged to get in touch with the PI for further details (ingmar.devries@unitn.it).

References

Clark, A. (2013) Whatever next? Predictive brains, situated agents, and the future of cognitive science. Behavioral and Brain Sciences 36, 181–204.
De Lange, F. P., Heilbron, M. & Kok, P. (2018) How Do Expectations Shape Perception? Trends Cogn Sci 22.
Friston (2010) The free-energy principle: a unified brain theory? Nat Rev Neurosci 11, 127–138
De Vries, I.E.J., Wurm, M.F. (2023) Predictive neural representations of naturalistic dynamic input. Nat Commun 14, 3858
De Vries, I.E.J., De Lange, F.P., Wurm, M.F. (2026) Hierarchical priors enable neural prediction of perceived biological motion. eLife 15, RP111118

The Laboratory of Autism and Neurodevelopmental Disorders at IIT (IIT-LAND), directed by Dr. Michael Lombardo, at the Center for Neuroscience and Cognitive Systems, Istituto Italiano di Tecnologia, Rovereto, invites applications for 1 PhD scholarship to investigate early biomarkers behind autism subtypes. Our research aims to understand how autism may be split into distinctive types of autisms, characterized by distinctive phenotypic presentation, underlying neurobiological mechanisms, and differential responses to treatment. To answer these types of questions, we use a combination of approaches from neuroimaging (EEG, MRI), cognitive and computational neuroscience, and data science. Our work is primarily focused on human patients (i.e. autistic children), but we also collaborate with other groups on larger cross-cutting translational work focused on elucidating biological mechanisms in model systems. For more info, see:  https://land.iit.it.

We have 1 PhD position focused on identifying biomarkers for different clinically and behaviorally distinctive subtypes of autism. The work heavily focuses on methodologies such as eye tracking, EEG, and MRI/fMRI. The datasets we work with are a combination of large publicly available datasets, datasets from international collaborators, as well as data coming from ongoing experiments run within IIT-LAND. The work will heavily rely on new or past stratification models of neural and phenotypically distinctive autism subtypes. The two positions are fully-funded off of an ERC Consolidator Grant to Dr. Michael Lombardo.

We are looking for talented and highly motivated individuals that can build on prior skill sets or knowledge within the core areas of our research - EEG, eye tracking, neuroimaging (MRI, fMRI), data science, and autism. Advanced understanding and conceptual thinking with regards to statistics and big data analysis is a plus, as is requisite computational and programming skills (e.g., R, Python, MATLAB) to implement such ideas. Ability to speak both Italian and English is highly prioritized. Good communication skills and ability to work within larger groups is also emphasized. Strong passion/desire to pursue an academic career focusing on neurodevelopmental disorders like autism is also a key characteristic we are looking for, as is an existing strong grasp of the literature on autism and neurodevelopmental disorders.

Successful candidates will join a growing diverse, multidisciplinary and collegial group, and will be offered direct training, supervision and mentorship from the principal investigator and other senior members of the lab. The work also offers up the possibility of working within a larger international context, as nearly all of the work we do on this topic is done with collaborations from colleagues in Europe and the USA. The position is a four-year scholarship in the international doctoral school in Cognitive and Brain Sciences (CIMEC) at the University of Trento. Candidates will join a diverse cohort of PhD students and receive multi-disciplinary training at the interface of computational, experimental and cognitive neuroscience across humans and animal models.

The IIT-CNCS in Rovereto is actively expanding its infrastructure for systems level neuroscience research. Our center is located in Trentino, a region of Northern Italy nested within the Dolomite mountains, offering easy access to spectacular natural beauty and mountaineering, vibrant culture and exceptional quality of life (https://www.iit.it/it-IT/cncs-unitn/).

Candidates can informally contact Dr Michael Lombardo (michael.lombardo@iit.it) to gather more information about the position, the project, the application procedure and the selection process.