The Center for Translational Neurophysiology of Speech and Communication (CTNSC) at the Istituto Italiano di Tecnologia (IIT) is looking for up to 4 highly motivated, full-time PhD students to work in the core research areas of the Center. The PhD student will work in Ferrara, in an international and multidisciplinary team including biomedical engineers, biologists, computer scientists, psychologists and medical doctors. The PhD positions will cover the following core areas of CTNSC. DEADLINE: 5TH AUGUST 2016 CTNSC Info [ITA/ENG]: https://www.iit.it/centers/ctnsc-unife PhD page [ITA/ENG]: http://www.unife.it/studenti/dottorato/concorsi/selection How to participate to the selection [ITA/ENG]:http://www.unife.it/studenti/dottorato/modulistica/concorsi/32-ciclo/neurosc... * Functional investigation of innovative neural interfaces Evidences show that using electrophysiological techniques is possible to extract information about brain processes and then translate these signals into commands that could be used to recover the lost capabilities. The purpose of the project is to investigate the in-vivo performance of novel devices - both in-house developed or obtained from collaborating laboratories - with a focus on i) enhanced capability to record neural signals; ii) large charge transfer capability to enhance the stimulation performance and iii) small size to minimize inflammatory reaction and gliosis. The candidate will be involved in the development of a stable and functional interface between living neural tissue and probes in rat model. Techniques: in-vivo single-unit recording and epicortical recording , histological techniques and image analysis, microscopy techniques and data analysis. Requirements: The candidate should have a background in one or more of the following fields: biology, medicine, pharmacology or related disciplines. Programming experience is appreciated but not mandatory. Familiarity with electrophysiological and/or microscopy techniques is of advantage. Contacts: Dr. Emma Maggiolini: emma.maggiolini@iit.it<mailto:emma.maggiolini@iit.it> Prof. Luciano Fadiga: luciano.fadiga@iit.it<mailto:luciano.fadiga@iit.it> * Animal neurophysiology investigation of sensorimotor functions The discovery of mirror and canonical neurons in monkey premotor and parietal cortex motivated a number of studies on how sensorimotor transformations in the brain may support understanding of action performed by conspecifics. This still constitute a fundamental area of research which is necessary to unravel the basic mechanisms of sensorimotor sharing during social interaction. The candidate working in this core area will investigate, in animal models, the neuronal activity of different (motor and somatosensory) cortical regions, pointing out their topographic organization as well as their role during observation, planning and execution of particular motor acts. Techniques: multidisciplinary approach involving behavioral testing, electrophysiological techniques (intracortical microstimulation, single-unit recording, field potentials recording, electromyography) and histological evaluations. Requirements: The candidate must have a background in the biological fields (biology, medicine, pharmacy and similar). At the end of the three-year period, the Ph.D. student will obtain deep knowledge and experience on in vivo neuroscience. Contacts: Dr. Riccardo Viaro: riccardo.viaro@iit.it<mailto:riccardo.viaro@iit.it> Prof. Luciano Fadiga: luciano.fadiga@iit.it<mailto:luciano.fadiga@iit.it> * Brain- and multimodal signal- based speech recognition Our approach to speech recognition is an "analysis by synthesis" approach which assumes that in order to recognize speech we need to understand the causal process (i.e., the speech production process) that stems from brain activity and, through coordinated movements of the vocal tract articulators, produces speech sounds. Such approach is largely motivated by work on speech perception carried out at CTNSC and serves two goals. The first goal is to build automatic speech recognition systems that, as humans do, work in very challenging scenarios (e.g., in the so called "cocktail party" scenario) and are able to learn how to recognize speech without relying on huge amount of carefully annotated speech data (as opposed to "data hungry" current recognition systems). The second goal is to recognize speech from one or more modalities that are within the speech production process, e.g., from brain signal or from visual and kinematic signals of the face and the vocal tract. Techniques: Machine learning, deep neural network, multimodal signal processing. Requirements: The successful candidate will have a degree in computer science bioengineering, physics or related disciplines. A background in machine learning and in speech and language processing. Contacts: Dr. Leonardo Badino: leonardo.badino@iit.it<mailto:leonardo.badino@iit.it> Prof. Luciano Fadiga: luciano.fadiga@iit.it<mailto:luciano.fadiga@iit.it> * Human Neurophysiology investigation of speech and communication abilities by means of micro-electrocorticography Historically, the study of speech processing has emphasized a strong link between auditory perceptual input and motor production output. The main aim of this area is to describe the neural systems involved in this sensorimotor representation linking speech perception and production. To this purpose, we use high-density surface microelectrodes for electrocorticography (micro-ECoG) to record electrical signals directly from the cortical surface in patients during awake surgery for low-grade glioma resection. Micro-ECoG is an important electrophysiological signal recording technique that combines high temporal resolution with good spatial localization. Techniques: Micro-ECoG, direct brain electrical stimulation, functional electrical mapping. Requirements: Applicants are expected to have a degree in biomedical engineering or basic/applied/health sciences. Requirements include a knowledge of neural signal processing and/or neuroimaging skills. Contact: Dr. Luciano Simone: luciano.simone@unife.it<mailto:luciano.simone@unife.it> Prof. Luciano Fadiga: luciano.fadiga@iit.it<mailto:luciano.fadiga@iit.it> * Human Neurophysiology investigation of speech and sensorimotor communication abilities by means of non-invasive techniques The neural mechanisms underlying speech and sensorimotor communication abilities, during real-life social encounters are mostly unknown. In the classic motor control frame of reference, individuals can be conceived as proactively building models of their action and of their sensory consequence. During interaction, these sensorimotor models can be extended to the social space whereby the control signal becomes the negotiated behavior of other people. The candidate will help in mapping the brain activities responsible for the emergence of such a shared behavior, in the domain of speech (phonological level) or action (upper arm movements). These experiments will inform the next generation of biologically inspired automatic communication recognition systems, essential to augment natural human-human coordination and promote the future of efficient human-robot interaction. Techniques: Electroencephalography (EEG), Electromyography (EMG), body motion kinematics (MoCap), Transcranial Magnetic Stimulation (TMS), transcranial Direct (tDCs) and Alternate (tACs) current stimulation. Requirements: The successful candidate will have a background in neuroscience, experimental psychology, computer science or engineering. Programming skills as well as a strong interest in cognitive neuroscience are fundamental. Electroencephalographic and kinematic data analyses skills are a plus. Contact: Dr. Alessandro D'Ausilio: alessandro.dausilio@iit.it<mailto:alessandro.dausilio@iit.it> Prof. Luciano Fadiga: luciano.fadiga@iit.it<mailto:luciano.fadiga@iit.it> [Description: cid:image001.jpg@01CC9EC9.BA36CB30] Emma Maggiolini, PhD IIT@unife, Center for Translational Neurophysiology Via Fossato di Mortara 17/19, 44121 Ferrara, Italy Tel. +39 0532 455983 SKYPE ID: lilmay75 e-mail: emma.maggiolini@iit.it<mailto:emma.maggiolini@iit.it> www.iit.it<http://www.iit.it/>