preferred start date: April 2025
Application Deadline: Remain open until the positions are filled.
No. of positions: 1
ABOUT THE POSITION:
RESPONSIBILITIES:
The SuPerWorld Research Group involves technology in pervasive computing and earth observation, which touches upon research that focuses on the real world towards (contributing in) making it more sustainable. As “real world”, we refer to humans, animals and plants, as well as to the physical and urban environment. As “pervasive computing”, we refer to sensing infrastructures and equipment that measure the real world, towards precise environmental monitoring and modelling. Web: https://superworld.cyens.org.cy/ The successful candidates will have the opportunity to conduct fundamental and/or applied research in the group’s areas of expertise, with a focus on computer vision and advanced AI techniques such as deep learning and will mainly work on the Horizon Europe PHENOWEX project (https://phenowex.eu), employing remote sensing techniques to perform high-throughput phenotyping of crops, understanding their resilience to climate change. The position holder should publish/present his/her research results in prestigious international conferences and journals and contribute to the centre’s key performance indicators. The successful candidate will work under the supervision and guidance of the SuPerWorld Research Group Leader, Dr Andreas Kamilaris. Responsibilities of Research Associate:
General Qualifications & Requirements:
- To apply novel AI techniques on various real-world challenges relating to environmental monitoring, protection and sustainability
- To contribute to the research activities of the group
- To contribute to a European-funded research project
- To prepare, submit and publish high-quality research papers
- BSc degree in Computer Science or in an area/field related to AI, computer vision, machine learning and/or deep learning.
- MSc degree in a specialization in data analysis, probabilistic modelling, earth observations, satellite imagery analysis and/or geographical systems is an advantage.
- Good coding skills (e.g. Python) is important.
- Knowledge of GIS tools is a plus (e.g. ESRI ArcGIS, QGIS).
- Confidence in mathematics (e.g., linear algebra, probabilistic methods).
- Proven experience with ML/DL frameworks (e.g. PyTorch, Keras).
- Knowledge of flying a drone with hyperspectral/LIDAR sensors will be considered an advantage.
- Self-motivation, ability to work independently, and excellent problem-solving skills.
- Prior publications in the area are desirable but not essential.
- Language requirements: Excellent written and oral English-language skills will be required.
- For non-EU applicants a work permit will be required
- Self-motivated with the ability to take initiative and work independently.
- Strong organizational, communication, presentation, and negotiation skills, having the ability to deal confidently and politely with enquiries.
- Very good analytical skills coupled with attention to detail.
- Dynamic, adaptable, hands-on and results driven.
- A team player with an ability to work independently and under pressure.
- High levels of commitment, energy, and drive.
- Excellent communication and interpersonal skills.
- Problem-solving
- High-quality research
- Strongly motivated/passionate with exceptional attention to detail.
- Team player and creativity are important skills due to the nature and philosophy of CYENS.
- Good presentation and communication skills
- A cover letter which clearly specifies 1) contact details, 2) employment availability date, 3) part-time or full-time availability
- A detailed curriculum vitae in English.
- Copies of academic transcripts
- Description of their academic and research experiences as well as any relevant industrial / innovation / entrepreneurship experience, where applicable (500 words maximum).
- Contact details of two University professors or one University professor and one industry referee who will provide the letters.
- Two (2) representative publications (if applicable).
- Two (2) representative innovation outcomes / products (if applicable).
