Post-Doctoral Research Fellow

(Applied Machine Learning)

University of Florida

 

Position Description:


The Florida Institute of Cyber Security Research (FICS) at the University of Florida is in search of a Post-Doctoral Research Fellow for participation in the NIH-sponsored “Uncovering and Surveilling Financial Deception Risk in Aging” led by Professors Natalie Ebner (Psychology), Daniela Oliveira (ECE), and Damon Woodard (ECE).  The team consists of researchers from the University of Florida, the McGill University, and York University, and seeks to advance scientific knowledge of the factors contributing to increased susceptibility to financial deception in the elderly population and to inform decision-supportive real-life interventions that adopt an age-targeted approach to reduce risk for financial fraud. Accomplishment of these goals demands extensive interaction between experts from applied machine learning (text, physiological measures, and brain imaging data), cyber security, engineering, psychology, and neuroscience. The candidate will also work in conjunction with graduate students and will be expected to publish in peer-reviewed journal/conference articles and assist in supervision of graduate students involved in the project.


The Post-Doctoral Fellow will provide expertise primarily in the area of applied machine learning, but ideal candidates should have experience in the following areas:


  1. Applied machine learning, natural language processing, especially for text and image data

  2. Design, implementation, and testing of software applications/programs (Python and JavaScript)


Experience/knowledge of cyber security, analysis of neuroimaging data, and experimental design are considered a plus.


The position is available immediately and for a period of up to three years.


Application Procedure:


  1. Interested applicants should send to Prof. Daniela Oliveira (daniela@ece.ufl.edu) and Prof. Damon Woodard (dwoodard@ece.ufl.edu) in an email and as a single pdf file: (i) cover letter explaining why the candidate is interested in the position and why they think they are a good fit for the position, (ii) CV, (ii) names of at least two references, and (iii) 2-3 published papers in the field of machine learning or applied machine learning.

  2. Only short-listed candidates will be notified about an interview.

  3. Application closes when the position is filled.