PhD Positions in Databases Data Science on Modern Hardware, TU Dortmund University

Interested in high-class research in the field of databases and modern hardware architectures?  As the Databases and Information Systems Group (DBIS Group) at TU Dortmund University, we're looking for talented, enthusiastic, and visionary

Research Assistants (PhD students)

At TU Dortmund University, we are exploring the use of modern hardware technologies, including multi-core processors, GPUs, and FPGAs, to accelerate database and Data Science tasks.  The DBIS Group is part of the Collaborative Research Center SFB 876 at TU Dortmund, a world-leading research effort in the Data Science field.

As a PhD student, you'd be part of that effort; you'd support our group in close collaborations with other groups in the department, but also with practitioners that need your help to handle vast amounts of data, e.g., from the LHC particle accelerator at CERN.

TU Dortmund University is among the largest and strongest universities in the metropolitan "Ruhr" area.  The Internet in Germany has its roots in the IT support center of our Computer Science department.

As a research assistant (PhD student), you'd be paid according to the TV-L 13 pay scale; roughly 40,000 EUR per year gross salary, plus attractive support for pension and health insurance.

For further information, please visit

http://dbis.cs.tu-dortmund.de/cms/en/home/jobs/

or contact Jens Teubner, jens.teubner@cs.tu-dortmund.de.





Download Official Call (pdf)

Applications enclosing the usual material may be sent until 03.03.2016 under reference number w18-16 to to:
Jens Teubner
DBIS Group, TU Dortmund University
Otto-Hahn-Strasse 14, 44227 Dortmund, Germany
jens.teubner@cs.tu-dortmund.de

PhD Scholarship in real-time bidding, computational advertising, and big data analytics, Florida Atlantic University

PhD Scholarship in real-time bidding, computational advertising, and big data analytics

The College of Engineering and Computer Science at Florida Atlantic University and the Bidtellect, a global leader in native advertising technologies and solutions, have recently teamed up to establish a "Bidtellect Laboratory" focusing on real-time bidding and computational advertising.

Applications are invited for two full-time PhD scholarships in real-time bidding, computational advertising, and big data analytics to start in August 2016 (or Spring 2017). The PhD positions are fully funded. Both students will work closely with the industry to design real-time bidding algorithms on commercial platforms which support billion level transactions on a daily basis.

Successful applicants should

1. Have an undergraduate (honors) or master degree (preferred) in computer science or related field (preferably with good knowledge in data mining, machine learning, mathematical modeling, and statistics).
2. Be familiar with big data analytics tools and platforms.
3. possess solid programming skills in Java, C/C++, etc.

The due date for Fall admission is February 15 2016 (International Students), and Spring admission deadline is July 15.

For general admission information, please to the following URL:
http://www.fau.edu/graduate/applyonline/international.php

For Computer Science and Computer Engineering PhD admission criteria, please refer to the following URL.

http://www.fau.edu/graduate/programs/docs/phd_computer_science.pdf
http://www.fau.edu/graduate/programs/docs/phd_computer_engineering.pdf

Interested applicants should send detailed Resume to Xinquan (Hill) Zhu (xzhu3@fau.edu).
Xingquan (Hill) Zhu
Dept. of Computer & Electrical Engineering and Computer Science
Florida Atlantic University
http://www.cse.fau.edu/~xqzhu

Two Postdoctoral research fellow positions at the University of Melbourne's Department of Computing & Information Systems

Join a world-class research group in one of two open postdoctoral research fellow positions at the University of Melbourne's Department of Computing & Information Systems, situated in one of the world's most liveable cities. Applications close end of February.

The first position is in adversarial machine learning. Little is known about how well state-of-the-art inference techniques fare when data is manipulated by a malicious adversary; this project aims to evaluate the robustness of broad classes of learners using tools from optimisation, and to explore consequences of robustness to computer security. This position is funded by an Elon Musk-backed grant from FLI. Further details:

http://jobs.unimelb.edu.au/caw/en/job/887407/research-fellow-in-adversarial-machine-learning

The second position is to research machine learning and systems. Topics span probabilistic databases, adaptive importance sampling, crowd sourcing, data integration, machine learning workflows. This position is funded by an Australian Research Council grant "Democratising Big Machine Learning". Further details:

http://jobs.unimelb.edu.au/caw/en/job/887416/research-fellow-in-machine-learning-systems

Both positions offer a competitive salary of $82k AUD plus 9.5% superannuation (PhD entry level A6). Applications close at the end of February via the links above.

For queries please email the project CI, Ben Rubinstein at benjamin.rubinstein@unimelb.edu.au Or visit http://bipr.net to learn more about the research group which has strong international collaborations and connections to industry. The CI will be at AAAI'16 this month.

Close date: 1 Mar 2016