Postdoctoral Research Fellow in Artificial Intelligence (ref. no. CaSToRC_PDF_24_01)

8 Feb 2024
Job Information

Organisation/Company

The Cyprus Institute

Department

CaSToRC

Research Field

Computer science
Engineering

Researcher Profile

Recognised Researcher (R2)

Country

Cyprus

Application Deadline

8 Mar 2024 - 00:00 (Asia/Nicosia)

Type of Contract

To be defined

Job Status

Full-time

Is the job funded through the EU Research Framework Programme?

European Union / Next Generation EU

Is the Job related to staff position within a Research Infrastructure?

Yes

Offer Description

Closing Date: 08/03/2024

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 Artificial Intelligence at CaStoRC. The successful candidate will conduct research in the application of existing and novel Artificial Intelligence and Deep Learning methods in cancer research.

More specifically, the successful candidate will contribute in research and development activities of the Agora 3.0 critical infrastructure project, in collaboration with the German Oncology Centre and several other research and industry partners in Cyprus. The project aims to establish a clinical trial unit at the German Oncology Centre, which will produce high quality medical imaging data from prostate cancer patients. The Postdoctoral Research Fellow will work closely with the GOC and a research team from the University of Cyprus to develop AI methods that will utilize medical imaging data to estimate the Gleason score and tumor stiffness through medical imaging.

The initial appointment is for a fixed-term period of 2 years 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:

Perform thorough literature review of the current trends and advancements in the use of AI in the medical imaging field and prostate cancer research.

Develop multimodal AI models which utilise high quality medical imaging and medical parameters data produced at the German Oncology Centre from prostate cancer patients to estimate Gleason score and tumor stiffness.

Analyze results and contribute to the preparation of research manuscripts.

Presentation of results in conferences and meetings and participation in journal publications.

Contribution to project (scientific) reporting & project management.

 

Requirements

Research Field

Computer science

Education Level

PhD or equivalent

Research Field

Engineering

Education Level

PhD or equivalent

Specific Requirements

Required Qualifications

PhD in Computer Science, Electrical / Computer / Computational Engineering, Physical Sciences or in a relevant field

Relevant publications in high impact journals or peer-reviewed conferences

Participation in top international scientific conferences

3-year relevant experience including PhD

Knowledge of AI frameworks (eg. PyTorch)

Programming Skills: Proficiency in programming languages, such as Python, commonly used in scientific computing and machine learning

Image Analysis Knowledge: Solid understanding of image processing and analysis techniques, including challenges specific to different types of imaging data

Experience in deep learning methodologies applied in imaging data and computer vision

Strong scientific and technical writing skills

Excellent knowledge of the English language, both verbal and writing

Demonstrated development ability, outstanding organizational, analytical, problem solving and communication skills

Excellent interpersonal skills and the ability to adopt to a multicultural/multinational environment

 

Preferred Qualifications

• HPC experience
• Statistical Analysis Skills: Competence in statistical methods relevant to imaging and data analysis

Languages

ENGLISH

Level

Excellent

Additional Information
Selection process

Application

For full consideration, interested applicants should process their application at The Cyprus Institute Exelsys Platform (https://bit.ly/3HDLRTw ) based on the instructions given. Applicants should submit a curriculum vitae including a short letter of interest, list of publications and a list of three (3) referees (including contact information) (all documentation should be in English and in PDF Format). For further information, please contact Dr Pantelis Georgiades ([email protected] ). Please note that applications which do not fulfill the required qualifications and do not follow the announcement’s guidelines will not be considered.

Recruitment will continue until the position is filled. 

The Cyprus Institute is an Equal Opportunities Employer certified from the Cypriot Ministry of Labor and also an HRS4R accredited Institution that adheres to the European Commission’s “Charter & Code” principles for recruitment and selection.

 

Contact person:Dr Pantelis Georgiades

Reference number:CaSToRC_PDF_24_01

Work Location(s)

Number of offers available

1

Company/Institute

CYI

Country

Cyprus

State/Province

N/A

City

Nicosia

Postal Code

2121

Street

Konstantinou Kavafi 20

Where to apply

Website

https://bit.ly/3HDLRTw

Contact

City

Nicosia

Website

http://www.cyi.ac.cy

Street

20 Constantinou Kavafi, Aglantzia, 2121 Nicosia

STATUS: EXPIRED