Department/faculty: Electrical Engineering, Mathematics and Computer Science Level: Master degree Working hours: 38 hours per week Contract: 4 years Salary: €2083 to €2664 per month gross Electrical Engineering, Mathematics and Computer Science The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) is known worldwide for its high academic quality and the social relevance of its research programmes. The faculty's excellent facilities accentuate its international position in teaching and research. The faculty offers an interdisciplinary setting for its 500 employees, 400 PhD students and 1700 undergraduates. Together they work on a broad range of technical innovations in the fields of sustainable energy, telecommunications, microelectronics, embedded systems, computer and software engineering, interactive multimedia and applied mathematics. EEMCS: Your Connection to the Future. The Department of Intelligent Systems (INSY) conducts research on processing, interpretation and securing of data to enable man and machine to deal with the increasing volume and complexity of data and communication. We have a strong focus on security, multimedia, and health sciences. The cybersecurity section in INSY is a collaborative effort with the Technology, Policy, and Management (TPM) faculty to solve complex security issues from both a computer scientist's and a policy maker's viewpoint. The cybersecurity research at INSY is focussed on secure data processing and machine learning: we aim to hide sensitive data by means of cryptography and to discover malicious activities through data analytics. We develop new algorithms and encryption schemes with applications in networks, forensics, healthcare, and vital infrastructures. We teach cryptography, data analytics, and cyber forensics courses in the Computer Science, Mathematics and Electrical Engineering graduate programme. Job description Under the guidance of Dr. Sicco Verwer you will research and develop the technology needed for semi-supervised learning of probabilistic timed automata (building upon http://repository.tudelft.nl/view/ir/uuid:61d9f199-7b01-45be-a6ed-04498113a212/). The algorithms developed will be used in a joint research project with Prof. VS Subrahmanian from the University of Maryland on fast activity detection in massive streams of timestamped observation data (see http://www.umiacs.umd.edu/research/CDIG/projects/adetect.html). Ongoing collaborations between the cybersecurity group and several industrial partners will provide computer network data that will be used to learn and detect timed patterns for cyber attacks and botnet traffic, amongst others in industrial control systems (SCADA) for critical infrastructures. You will: • Improve and implement state-of-the-art state machine (automata) learning algorithms. • Use these algorithms to enhance the security of computer systems and society. • Write scientific papers describing this work. • Join an enthusiastic team of researchers working on learning state machines (automata) for cyber security. • Participate in the TU Delft graduate school. • Work towards obtaining a PhD degree. Requirements We invite applicants who meet the following requirements: You have an MSc. degree in computer science, artificial intelligence, or mathematics. You have excellent programming skills. You are enthusiastic about (state) machine learning and security. You have a good understanding of spoken and written English. Having some background in network security, machine learning, or probabilistic modelling is a plus. Conditions of employment TU Delft offers an attractive benefits package, including a flexible work week, free high-speed Internet access from home (with a contract of two years or longer), and the option of assembling a customised compensation and benefits package (the 'IKA'). Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities. As a PhD candidate you will be enrolled in the TU Delft Graduate School. TU Delft Graduate School provides an inspiring research environment; an excellent team of supervisors, academic staff and a mentor; and a Doctoral Education Programme aimed at developing your transferable, discipline-related and research skills. Please visit www.phd.tudelft.nl for more information. Information and application For more information about this position, please contact Dr. Sicco Verwer, phone: +31 (0)15-2788435, e-mail: S.E.Verwer@tudelft.nl To apply, please e-mail a detailed CV along with a letter of application by 31 August 2014 to Ms. C. Kohlmann-van Noord, Hr-eemcs@tudelft.nl. When applying for this position, please refer to vacancy number EWI2014-18.
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