Computational Scientist(s) (ref. no. CaSToRC_PDF_21_03)

The Cyprus Institute (CyI) is a non-profit science and technology educational and research institution based in Cyprus and led by an acclaimed Board of Trustees. The research agenda of CyI falls within the following four research centers: The Computation-based Science and Technology Research Center (CaSToRC); the Science and Technology in Archaeology and Culture Research Center (STARC); the Energy, Environment and Water Research Center (EEWRC); and the Climate and Atmosphere Research Center (CARE-C). Considerable cross-center interaction is a characteristic feature of the Institute’s culture.

This job opening is within CaSToRC of CyI. CaSToRC is a member of the Pan-European Centre of Excellence for “Research on AI- and Simulation-Based Engineering at Exascale” (RAISE) that encompasses the complementarity of HPC and AI technologies to address engineering challenges and optimize processes of ever-growing complexity. This new Centre of Excellence was launched on 1^st January 2021 and it comprises of the Jülich and Barcelona Supercomputing Centres in Germany and Spain, respectively, which host some of the most powerful supercomputers in the world, the European Organization for Nuclear Research (CERN), as well as leading industrial and academic partners across Europe, including Iceland, France, Switzerland, Belgium and Latvia. RAISE will be an enabler for the advancement of these technologies in Europe on industrial and academic levels, and a driver for novel intertwined AI/HPC methods. These technologies will be advanced on the basis of representative use cases, covering a wide spectrum of academic and industrial applications, for example wind energy harvesting, hydrodynamics of wetting, seismic imaging, manufacturing, physics, turbomachinery and aerospace. Within the Center of Excellence, CaSToRC is engaged in two research projects in the areas of wetting hydrodynamics and seismic imaging, described below in detail. CaSToRC invites applications from scientists to work in either of these two projects.

The appointment will be at the Post-Doctoral Research Fellow or Associate Research Scientist rank, depending on the successful candidates’ qualifications and level of experience. The initial period of the appointment will be up to 2 years, renewable, subject to availability of funding. An internationally competitive remuneration package will be offered, according to the level of experience of the successful candidate(s). The successful candidate will have the opportunity to attend training events and present at prestigious conferences globally.

Responsibilities

The successful candidates will work at CaSToRC and will be engaged in research activities on innovative AI methods for heterogeneous HPC architectures capable of scaling towards Exascale pertaining to one of the following research projects:

1. Perform simulations and employ physics-informed machine and deep learning algorithms in computational fluid dynamics, in an effort to understand the behavior of liquids on surfaces;
2. Work on the optimization of seismic imaging methodologies using AI, simulation and data assimilation approaches to accurately delineate subsurface structures. This work will be in close collaboration with the Delphi consortium of geo-energy and geo-imaging companies.

Applicants are encouraged to indicate their preferred project in their letter of interest.

In relation to the above-mentioned projects, the successful candidates will be engaged in the following:

1.       Code development optimized for compute- and data-intensive workflows

2.       Prepare deliverables, scientific reports and manuscripts related to the project outputs

3.       Contribute to the co-supervision of PhD students who may be engaged in related projects

4.       Coordinate with other members of the RAISE consortium, as well as with members of the broader user communities

5.        Engage in dissemination and outreach activities to publicize the project outcomes.

6.         Write proposals for accessing computational resources