Postdoctoral Research Fellow in Data-Driven Computational Science (ref. no. CaSToRC_PDF_23_05)

The Cyprus Institute (CyI) is a European non-profit Science and Technology oriented Educational and Research Institution based in Cyprus and led by an acclaimed Board of Trustees. The research agenda of the CyI is pursued at its five Research Centres: The Computation-based Science and Technology Research Centre (CaSToRC), the Science and Technology in Archaeology and Culture Research Centre (STARC), the Energy Environment Water Research Centre (EEWRC), the Climate and Atmosphere Research Centre (CARE-C), and the Science and Technology Driven Policy and Innovation Research Centre (STeDI-RC). Considerable cross-centre interaction is a characteristic of the Institute’s culture.

The Cyprus Institute invites applications for a highly qualified and motivated individual to join the Institute as a Postdoctoral Research Fellow in Data-Driven Computational Science at CaStoRC. The successful candidate will conduct fundamental research in one or more of the following areas:

• Data mining methods
• Complex network analysis
• Deep learning architectures
• Cross-disciplinary applications of “big data” methods in climate science, smart farming, education, health, etc

The candidate will be working primarily with Prof. Constantine Dovrolis (recently moved to CyI from Georgia Tech -- see http://www.cc.gatech.edu/~dovrolis/).

This position offers a unique opportunity for fundamental research and its exact focus will be determined also based the interests and skills of the successful candidate. The successful candidate will also work closely with the PI in writing relevant grant proposals.

The appointment is for a fixed-term period, with the possibility of renewal subject to performance and the availability of funds. An internationally competitive remuneration package will be offered, which is commensurate with the level of experience of the successful candidate.

Responsibilities/activities to be involved in:

1. Development of novel methods in any of the following: data mining, complex network analysis, machine learning/AI, data-driven computational science.
2. Collection and statistical analysis of data from various application domains.
3. Writing research papers in collaboration with the PI -- aiming to publish at top-tier conferences and journals.
4. Presentation of results in conferences and meetings and participation in journal publications.
5. Contribution to research proposal preparation, project (scientific) reporting & project management.
6. Supervision and guidance of Research Assistants and Students.