Position: Opening for a Postdoctoral Research Fellow to work on developing novel statistical methods for multi-modal data generated by #wearables. The embedding of multiple sensors in wearable devices now allows real-time tracking of sleep, physical activity, heart rate, and more to come. This comprehensive multimodal tracking requires a next generation of statistical methods – the primary focus of this fellowship. The fellow will be mentored by Dr. Vadim Zipunnikov and will be a part of the Wearable and Implantable Technology (WIT) group at the Department of Biostatistics at the Johns Hopkins Bloomberg School of Public Health.
Duties and Responsibilities: The successful applicant will work primarily on developing and testing novel statistical methods for modelling and fusing functional, matrix-variate, and time-series data. The applicant will also have an opportunity to work on a collaborative project with Takeda Pharmaceuticals with a focus on identifying clinically relevant characteristics and patterns of actigraphy-measured physical activity and their relationship with cognitive, behavioral, and physiological endpoints in subjects with and without mild Alzheimer’s.
Qualifications: Applicants must have a PhD in biostatistics, statistics, computer science, applied mathematics, biomedical informatics, or any other field related to data science. Strong programming skills in R or Matlab are essential.
To apply, please send a CV and contact information for references to:
Vadim Zipunnikov, PhD
Associate Professor
Department of Biostatistics
Johns Hopkins Bloomberg School of Public Health
615 North Wolfe Street, E3644
Baltimore, MD, 21205-2179
work phone: (410) 502-9309
email: vadim.zipunnikov@gmail.com