Connectionists: Postdoctoral position at New York University (ML for healthcare)

[Carlos Fernandez-Granda]

A postdoctoral position is available in the laboratory of Carlos
Fernandez-Granda <https://cims.nyu.edu/~cfgranda/pages/projects.html> at
the Courant Institute and Center for Data Science at NYU. The focus of the
position is the design of deep-learning methodology for medical
applications, with emphasis on domain adaptation, high-dimensional signal
processing, and semi-supervised learning. The developed techniques will be
applied to automatic quantification of rehabilitation dose in stroke
patients from sensor and camera data, in collaboration with the Mobilis Lab
<https://urldefense.proofpoint.com/v2/url?u=http-3A__www.mobilislab.com_&d=DwMFaQ&c=slrrB7dE8n7gBJbeO0g-IQ&r=0CDTSVf_Hx57Tlq-sIkppasosNJ6kN7twD37CbtHhXI&m=bRzheAZ06GkR95rswLnxgN-3WMG7cfEMwzachOrHJUY&s=6J4BY60uCouPSmzGeAAamjG2S1dHwPqD-MIcpIWzuWQ&e=>
in the Department of Neurology at NYU School of Medicine, which aims to
enhance motor recovery after stroke.

Qualifications

Candidates should possess a Ph.D. in Computer Science, Electrical
Engineering, Data Science, or related disciplines. In addition, they should
have a strong background in machine learning, experience with deep
learning, solid programming skills and an interest in healthcare. They must
have the ability to work independently and with an interdisciplinary team.

Application instructions

The position is available immediately, and is renewable yearly for up to
three years. Interested candidates should submit (1) a CV, (2) a brief
cover letter explaining their research experience, how their interests
would fit the goals of the project, career plans, and available start date,
and (3) the names and contact information of three references familiar with
the applicant’s research and academic work to cfgranda at cims.nyu.edu

Link: https://apply.interfolio.com/66997
<https://urldefense.proofpoint.com/v2/url?u=https-3A__apply.interfolio.com_66997&d=DwMFaQ&c=slrrB7dE8n7gBJbeO0g-IQ&r=0CDTSVf_Hx57Tlq-sIkppasosNJ6kN7twD37CbtHhXI&m=bRzheAZ06GkR95rswLnxgN-3WMG7cfEMwzachOrHJUY&s=EECioKtq-twqwgd176gEdSBF4Y_Bfl0464GbJbemqYc&e=>
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