Call for doctoral students

New call for doctoral students January 2015. We will hire 2-3 new doctoral students in this call.

Place your application in HICT home page.

1. Mobile crowdsensing and mobile cloud computing

Develop new methodology and techniques for scalable mobile crowdsensing and intelligent data analysis of large-scale heterogeneous datasets in ubiquitous cloud environment, provide modular re-usable instruments for distributed mobile computing systems, evaluate the solutions through prototypes and public deployment, publish research results in high-quality international journals and conferences, and increase competence in Europe in theoretical and experimental areas of mobile computing.

Required qualifications:

  • M.Sc. in CS, EE, information science, or other relevant discipline
  • 2+ years experience in Java, C++, Python, or other languages appropriate for building distributed and pervasive systems
  • proficiency with Linux
  • strong written and verbal communication skills in English

Preferred qualifications:

  • 1+ year experience with data mining, machine learning, statistical modeling tools and underlying algorithms, OR
  • familiar with open cloud platforms like OpenStack, OR
  • 1+ year experience with Hadoop and mainstream ecosystem projects (Hive, Pig, HBase, etc.), OR
  • experience with networking performance measurement, analysis and optimization, expecially the networking performance in virtualized environment, OR
  • 1+ year experience with mobile app development for smartphones and wearable devices like Google Glasses and Samsung Gear, OR
  • hands-on experience with computer vision algorithms, especially the ones for 3D-reconstruction

2. Adaptive Mobile Multimedia Systems

The student will develop optimized solutions for mobile multimedia services with an emphasis on adaptive video streaming. The goal is to optimally balance resource consumption with the quality of experience through adaptive protocols, intelligent content/service management, and user behavior analytics.

Required qualifications:

  • M.Sc. in CS, EE, physics, mathematics, or other quantitative discipline
  • intermediate knowledge in statistics
  • some experience in using R or Matlab
  • basic programming skills
  • basic knowledge of network protocols

Preferred qualifications:

  • some experience in stochastic modeling
  • some knowledge in statistical learning
  • intermediate knowledge of network protocols, especially for multimedia streaming

3. Software tools for developing protocols for bacterial nanonetworks

The area of molecular communications is a highly-interdisciplinary research area, where the aim is to create communication networks at the nanoscale using biological components/systems. This PhD topic will cover a specific area of molecular communication which is bacterial nanonetworks, where bacteria will be utilized as infomation carrier between nanomachines.

The PhD work will cover theoretical modeling and simulation of communication protocols in bacterial nanonetwork. The candidate is NOT required to have any background in molecular biology, where most concepts can be acquired from good literature reading. The PhD candidate will also have an opportunity to work and collaborate closely with wet lab biologists in order to enhance their knowledge in molecular biology, as well as validate their theoretical models with the wet lab experiments.

Required qualifications:

  •  M.Sc. in CS, EE, physics, mathematics, or other quantitative discipline
  • experience in mathematical frameworks such as Matlab, Octave or R
  • good working knowledge of Java, and or C++
  • background in communication networking protocols

 Preferred qualifications:

  • strong background in mathematical foundations of computer science, including graph theory, optimization theory, stochastic modeling, and game theory
  • experience of simulation packages such as Opnet, NS3
  • previous experience in modeling and simulation of sensor networks (ideal, but not necessary)
  • good knowledge of English (speaking, reading and writing)

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