We are inviting applications from Postdoctoral fellows who are interested in applying for national-level support for hosting postdocs or any similar modes of funding. We are interested in supporting their application and would be happy to host them depending on mutual agreement. Postdoctoral positions will be hosted at IIT Jodhpur School of AIDE under Cognitive Science Research Initiative (CSRI) / National Postdoctoral Fellowships (NPDF)/DBT-Welcome early career schemes 2022-23. If you are interested in applying, please forward me your CV and a one-page research proposal.
Some of the current projects in the lab are listed. Candidates with a Ph.D. in Neuroscience, Cognitive Science, Biotechnology, Biomedical Engineering, Computer Science, Electrical Engineering, Physics, Mathematics, and Statistics are strongly encouraged to apply. Additionally, they must have a strong computational background with an interest and passion for Cognitive Neuroscience. Familiarity with statistical techniques, Signal processing, and knowledge of programming in Matlab/Python/C/C++ is essential.
Applying whole-brain large-scale Computational models/Machine learning/Deep learning models and algorithms to characterize normal versus pathological dynamical states (health vs. disease), memory and perceptual processing, Multisensory speech processing, aging brain dynamics, and brain networks classification in ASD, ADHD. This is a data-driven modeling project and requires programming skills, interest in systems neuroscience, and cognition.
EEG, fMRI data acquisition in resting state, working, and episodic memory across different age groups to understand age-associated neural correlates of cognitive decline. We develop computational methods using nonlinear dynamics, signal processing, and graph theory to understand dynamic functional connectivity, cognitive and neural flexibility, and age-associated reorganization.
We have an immediate opening at the Senior Research Fellow (SRF) level in my Lab at the Indian Institute of Technology, Jodhpur School of Artificial Intelligence & Data Science, to work on an exciting project on tACS modulation of causal effects on perceptual variability during multisensory integration (MSI) using AV stimuli and source EEG brain connectivity and dynamics. This project starts in April and will continue for 3 years.
This multimodal approach, utilizing non-invasive human neuroimaging data recording from the brain via fMRI, EEG/MEG, and detailed large-scale computational models, will establish links between neurotransmitter imbalance and the organization of large-scale anticorrelated neural systems, cognition, and symptoms (broadly speaking, cognitive impairment) associated with impaired cognition in humans. This study will be conducted at the National Brain Research Center, involving fMRI data acquisition primarily in the resting state and simple tasks from participants across a range of age groups. EEG/MEG component of the data acquisition will also take place at NBRC.
This project requires setting up behavioral experiments, EEG acquisition, and analysis. A possibility of collecting behavioral data inside the scanner. We have two 64-channel EEG recording facilities along with two different Eye tracking systems. This study also uses big data repositories such as CAMCAN, ABIDE, etc. for building a large-scale computational model to explore the computational mechanisms underlying cortical-subcortical interactions (Shastry et al., 2022; Pathak et al., 2022; Thuwal et al., 2021; Das et al., 2021; Shaoo et al., 2020).
For example, an in-depth analysis of statistical issues involved in studying fMRI dynamics revealed surprising results, e.g., spectral graph theoretic and graph diffusion models explain fMRI dynamics and capture individual subject variability better than nonlinear biophysical models (Ghosh et al., 2021; Kumar et al., 2020; Surampudi et al., 2019; Surampudi et al., 2018). While the previous examples are specific to neuroimaging, we have also developed general methods applicable beyond neuroimaging to characterize EEG/MEG source and sensor-level dynamics, which may find diverse applications.
Brain state dependent stimulations, feedback and modulation of neurophysiological responses and oscillatory changes. For example, does the regulation of local excitation-inhibition balance aid in recovery of functional connectivity and change in endogenous brain states to alter perceptual variability and sensitivity during perception, memory and attentional processing (Roy et al., 2021; Naskar et al., 2021; Vattikonda et al., 2016; Dagar et al., 2016).