Available grants vary from 1509.80 to 989,70 euro net per month (for candidates holding a PhD or an MSc degree, respectively) for periods extensible up to 24 months. Efforts are being made to obtain further financing so as to extend the period of the grants. Please contact the people listed below for the specific details of each of the grants.
Ref. C4_WP1.2 | Security by Construction in Cloud and Internet of Things Ecosystems
Research fellowship to supervise the pursuit and the quality of the research activities on security by construction in cloud and Internet of Things ecosystems, as well as for the execution of parts of those works, which include the research of ways to establish the guarantee of security in software systems by construction, focusing mainly on software design and development processes (security engineering). It also includes the prototyping of a set of software tools for security engineering, attack modelling, and semi-assisted testing.
Ref. C4_WP1.3 | Fault Tolerance in Cloud and Internet of Things Ecosystems
Research fellowship to carry out work in a project about fault tolerance in cloud and Internet of Things ecosystems. The goal of the project is to explore fault tolerant mechanisms for cloud-based mobile applications. The work plan includes the prototyping of a set of tools for fault tolerance that may be added as a service configurable according to application specificities.
Ref. C4_WP2.2 | Passing cloud
The successful candidate will research and develop algorithms and applications for the development of a framework to identify, predict, monitor and warn on constraints and risks for road traffic. Therefore, it is expected that the applicant has and is able to further develop research and development skills on mobile applications, integration of Artificial Intelligence technologies, and Cloud Computing technologies. It is also expected that the successful candidate is able to perform some administrative tasks related with the scientific management of the project. The successful applicant will also be responsible for accompanying the development of research work with graduate and undergraduate students and junior researchers, and of contributing to the writing of research projects in this area.
Ref. C4_WP2.5 | Cloud Based Image/Video Coding: Improving efficiency and QoE
The work plan includes scientific and technological research tasks carried out in order to design and implement a cloud-based holographic and plenotic coding method, which allows a good performance of the encoder in relation to encoding time, throughput and QoE. The candidates should have a degree in Computer Science, or Computer Engineering, or Electrical and Computer Engineering or equivalent. Special relevance will be given to candidates with experience in Image and video coding and Quality of Experience on Multimedia.
Ref. C4_WP3.2 | Big Text to Knowledge (BText2K)
Research fellowship to pursue research work on the extraction of knowledge from unstructured text, especially the huge amounts of text (“Big Text”) stored in, or flowing through, large infrastructures like a cloud or the Web. In particular, there is a high interest in the extraction of binary relations between named-entities and relations that characterize entities. This kind of relations are of great relevance, being fundamental for multiple advancements in Natural Language Processing, and also with many interesting applications in different areas of Artificial Intelligence.
Ref. C4_WP3.3 | Omics data analysis
Research fellowship to support R&D activities in the field of health sciences in close collaboration with CICS-UBI. We welcome candidates from the Computer science field who have basic knowledge in molecular biology, and candidates from the Biological sciences field who have basic knowledge of bioinformatics. The successful candidate will have the opportunity to work on multi-disciplinary projects involving omics data, including genomics, transcriptomics, proteomics and metabolomics. The candidate will be responsible for providing bioinformatics support including data management and analysis of high throughput sequencing data from next-generation sequencing. The successful candidate will have the opportunity, if desired, to carry out wet lab work.