Funded PhD position in Machine Learning - UNSW Sydney

Funded PhD position in Machine Learning - UNSW Sydney

de către Michael Siebers-
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UNSW Sydney, Australia, School of Computer Science and Engineering 
Position: PhD student, Full time, Research area: Machine Learning/Artificial Intelligence

The School of Computer Science and Engineering, UNSW Sydney, Australia is offering a funded PhD position in Machine Learning and Artificial Intelligence. The successful applicant will work with classification and quantification methods in a real-world application of estimating the density of insect vectors and pests using optical sensors, among other applications. The research will deal with challenging scenarios for classification and quantification algorithms such as concept/context drift, imbalanced classes and streaming data. 

The School of Computer Science and Engineering is one of the largest and most prestigious computing schools in Australia. For further information about the School, please visit http://www.cse.unsw.edu.au/

Requirements: A successful applicant should have solid programming skills, introductory knowledge of machine learning, ability to work in an interdisciplinary field, good analytical skills, and proficiency in English. Candidates must have a Bachelor or Master degree in Computer Science or related area.

How to apply: All applications should be sent to Gustavo Batista (gbatista@cse.unsw.edu.au). Your application should include a 1-page motivation letter, a short CV, copies of all transcripts, degrees, English test result (if available), publications (if any), and names and contact details of at least two referees. 

Key dates: For fullest consideration, applications must be submitted by 1 August 2019. Applications will be accepted until the position is filled. Expected starting date is Term 1 (February) 2020.

CRICOS Provider Code 00098G.

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Prof. Dr. Gustavo E.A.P.A. Batista
Departamento de Ciências de Computação
Universidade de São Paulo
Campus de São Carlos
http://www.icmc.usp.br/pessoas/gbatista