The Unit of Engineering in Information and Communication Technologies (ETIC) (https://www.upf.edu/etic/) at the Pompeu Fabra University in Barcelona is opening an academic position in Machine Learning.

ETIC has a highly interdisciplinary research environment with faculty interests covering a broad range of topics that can be broadly grouped into four main areas where data-driven research is transversal to all of them: (http://www.upf.edu/web/etic/research)

Multimedia Technologies, covering topics in image processing and cinematography, sound and music computing, human-computer Interaction, graphics and educational technologies and cognition as it relates to multimedia.

Computational Biology and Biomedical Systems including topics such as computational neuroscience, analysis of biomedical data, nonlinear signal analysis in biological systems, instrumentation and biomedical electronics, computational simulation and biomechanics, medical imaging and modeling of complex biomedical systems.

Computation and Intelligent Systems covering foundations of computer science, several aspects of artificial intelligence such as planning, natural language processing, computer vision, machine learning, ubiquitous computing, information retrieval and data mining, and human cognition and its relation to robotics. 

Networking and Communications with topics related to both wired and wireless networks, network science, information theory and coding, as well as policy aspects and strategies related to networking technologies.

Currently ETIC is strengthening its research interests in these four areas with special interest in Machine Learning. We are looking for a junior scientist with strong research interests in any of these areas but with special focus in Machine Learning, and we seek applications for a Tenure-Track position. The appointed applicant will progressively lead a new research group, in close collaboration with the existing ones, being involved in the undergraduate and postgraduate teaching duties of the Department, in particular with the deployment of the new Degree in Mathematical Engineering of Data Science.

Candidates should hold a PhD degree and have an excellent scientific-technical background in Machine Learning, including (but not restricted to) topics such as Multimedia Technologies, Computational Biology and Biomedical Systems, Computation and Intelligent Systems or Networking and Communications. The candidate should also have interest in confronting and resolving scientific problems/challenges, and leading several research publications in major journals.

A motivation letter, curriculum vitae, list of publications, research plan and addresses of three putative referees should be sent as a single pdf to [email protected], before March 24th 2017.