Postdoc in applied mathematics and data analysis | Luxembourg City, Luxembourg | University of Luxembourg

Position:	Postdoc in applied mathematics and data analysis
Institution:	University of Luxembourg
Location:	Luxembourg City, Luxembourg
Duties:	Using arange of mathematical tools, this project aims to improve our understanding of how DBS affects the brain. It combines all available datasets in the project to create models capturing patient-specific and personalized brain dynamics before and after DBS stimulation. Models will capture stimulation at a wide range of frequencies, pulse widths and amplitudes across different contact configurations. Data includes EEG, peripheral sensors (such as accelerometers), LFPs and clinical data. Changing stimulation parameters will give us a nonlinear view of changes in brain connections. This will build new hypotheses on the effect of DBS stimulation on different areas of the brain and help us predict effective stimulation parameters
Requirements:	Hold a Ph.D. degree in (applied or theoretical) mathematics, theoretical physics, engineering, or computer science. Candidates must have a publication record in data analysis and machine learning. Experience in computational neuroscience is a plus. Excellent working knowledge of English is required

Text:	Postdoc in applied mathematics and data analysis Using arange of mathematical tools, this project aims to improve our understanding of how DBS affects the brain. It combines all available datasets in the project to create models capturing patient-specific and personalized brain dynamics before and after DBS stimulation. Models will capture stimulation at a wide range of frequencies, pulse widths and amplitudes across different contact configurations. Data includes EEG, peripheral sensors (such as accelerometers), LFPs and clinical data. Changing stimulation parameters will give us a nonlinear view of changes in brain connections. This will build new hypotheses on the effect of DBS stimulation on different areas of the brain and help us predict effective stimulation parameters Hold a Ph.D. degree in (applied or theoretical) mathematics, theoretical physics, engineering, or computer science. Candidates must have a publication record in data analysis and machine learning. Experience in computational neuroscience is a plus. Excellent working knowledge of English is required