Fully-funded PhD Positions in Automatic Emotion Recognition at SUNY
 
Application deadline: 22 March 2017 (**see below for more information**)    

We have several PhD research assistantship positions available at the State University of New York, Albany. We are seeking highly creative and motivated applicants with a keen interest in doing research in human-centered technology, affective computing, and automatic emotion recognition using machine learning and multimodal signal processing techniques.  

Requirements: - A bachelor's degree in a relevant field (Electrical and Computer Engineering, Computer Science, Statistics, or related) - Solid background in computer programming - Proficiency in spoken and written English - (Preferred) Knowledge in the following technologies: MATLAB, Python, Java, Perl, C++, Unity - (Preferred) Previous coursework and/or practical experience in machine learning - (Preferred) Solid background in mathematics and/or statistics     Interest in one of the following areas: - Human-Centered and Affective Computing, Computational Human Behavior Analysis - Machine Learning, Statistics, Applied Mathematics - Speech Processing, Computer Vision  
 
We expect: - Keen interest in top level conference and journal publications - Self-organized, team worker, with good communication skills  
 
We offer: - You will work at one of the leading U.S. Universities and have the opportunity to work towards your PhD in a group of excellent scientists - Tuition, stipend, and fringe benefits - You will get financial support to attend and present at top level international conferences - Visas will be fully funded for international students    

To apply, please send an email to Prof. Yelin Kim (yelinkim@albany.edu) including a CV and a research statement (max. 2 pages) by March 22, 2017. We have rolling admissions policies, so please apply as early as possible. Please give your email the subject “SUNY PhD Research Assistantship in Automatic Emotion Recognition.'    

Please liberally forward and share to possibly interested candidates or people that might know suitable candidates.