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PhD Student Positions in Brain Networks (Canada)
|Posted Thursday, November 10, 2016|
Applications are invited for two PhD students to join the Brain Networks and Neurophysiology (NetPhys) Lab in Dalhousie University. The degree is multidisciplinary with options of admission through different graduate departments (Physics, Computer Science, Medical Neuroscience, Psychology and Neuroscience).
The NetPhys Lab is dedicated to understanding the behavioral relevance of neural communication in large-scale brain networks. We use pain as our modality for understanding how the brain processes internal and external information to generate perception. We also observe how ongoing mental processes alter pain perception. Our overall goal is to establish the scope and limits as to which we will be able to use brain imaging for predicting complex behavior such as pain. Our core focus is on predictive analytics geared at using multimodal brain imaging data to develop tools that can predict treatment outcomes, especially in chronic pain patients in all ages and across the lifespan. Other projects will study brain networks in altered states of consciousness—such as general anesthesia or mindful-awareness meditation—in multimodal data.
The planned studies will use leading-edge-imaging methods to analyze multimodal data (MEG, EEG, fMRI, DTI and EEG) combined with quantitative data analysis with a special focus on intrinsic and dynamic brain networks. We will use opensource resting and task related data to build new knowledge on brain function. This is thus a unique opportunity to contribute to the scientific models of the brain and to build transferable skills such as use of multimodal brain imaging, machine learning, dynamic connectivity and graph theory based network analysis in predictive analytics.
The student will learn how to use high dimensional data and cognitive neuroscience to develop neuropsychiatric biomarkers.
Applicants should submit a cover letter stating their research interests and current CV (including a list of scholarly publications), along with the names and contact information for three referees to Javeria.Hashmi@dal.ca asap.
The NetPhys lab is based in the Department of Anesthesia, Pain Management and Perioperative Medicine at Dalhousie University. Brain imaging projects will be conducted in collaboration with the leading neuroimaging facility in the Canadian Atlantic region (http://www.bioticimaging.com/) and The Big Data Institute https://bigdata.cs.dal.ca/ and with several other departments. You will work in collaboration with neuroscientists, computer scientists and clinical research experts.
Halifax is a port city, rich with culture and history, and is encircled in extraordinary coastal line and landscapes. The city has a bustling academic environment with six major universities located in the city municipality. It offers opportunities to think creatively, learn in a nurturing environment and to explore pristine nature.
We encourage students from all backgrounds including international students, women and minorities to apply.
Follow us @netphys1 and see #NetPhysJC on twitter
The student needs to have demonstrated academic excellence, proficiency in writing code and should have strong analytical skills in processing data (especially time series data), writing code in BASH and in at least one of the following packages: Matlab/Python/R.
Experience in machine learning, computational modelling, mathematical modelling is a big plus. This ideal candidate will have undergraduate or Masters level training in physics, electrical engineering, biomedical engineering, statistics or will have already demonstrated excellence in neuroimaging (fMRI, MEG/EEG).
We are especially interested in a devoted interest in the brain and motivation to gain expertise in advanced quantitative data analysis.
The successful candidate will be well organized, will demonstrate a thorough and conscientious approach to performing her/his duties, be a compassionate and strong team player and will be able to handle multiple tasks simultaneously.
Javeria Ali Hashmi