Job Search and Career Advice Platform

Enable job alerts via email!

Research Associate

KHALIFA UNIVERSITY

United Arab Emirates

On-site

AED 60,000 - 120,000

Full time

Today
Be an early applicant

Generate a tailored resume in minutes

Land an interview and earn more. Learn more

Job summary

A leading research university in the United Arab Emirates is seeking a Researcher to provide high-quality research support focused on agricultural technology. Responsibilities include conducting significant research, mentoring students, and ensuring timely publication of results. The ideal candidate will work on innovative tasks such as applying deep learning algorithms for plant disease monitoring and contributing to agricultural advancements using cutting-edge technologies. This is a full-time, permanent position with a focus on impactful research.

Qualifications

  • Ability to publish research in leading journals.
  • Experience in conducting experiments and documenting results.
  • Skilled in mentoring students.

Responsibilities

  • Conduct high-quality research aimed at publication.
  • Engage in scientific research as a team member.
  • Develop solutions for monitoring crop diseases.

Skills

High quality research support
Presentation skills
Scientific research engagement
Deep learning algorithms
Data fusion techniques
Job description

Organisation/Company KHALIFA UNIVERSITY Research Field Computer science Engineering Engineering Researcher Profile Recognised Researcher (R2) Established Researcher (R3) Country United Arab Emirates Application Deadline 31 May 2027 - 00:00 (UTC) Type of Contract Permanent Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

Offer Description

Job Purpose

  • To provide high quality research support and undertake internationally competitive research aimed at publication thereby contributing to the academic and research mission of the University.
  • Ability to present research plans and findings in a convincing style, both in oral and written modes of communication.

Strategic Responsibilities

  • Engages in scientific research as a professionally accountable member of the research team, actively participating in problem definition, planning, and execution of the research approach. In addition, undertakes responsibilities such as conducting experiments, interpreting findings, documenting and reporting results and progress, maintaining meticulous research records, and ensuring compliance with KU policies and procedures.
  • Conducts regular meetings with the Supervisor to convey research outcomes, review project focus, address concerns, troubleshoot issues, and effectively manage expectations.
  • Ensures timely publication of research results in leading journals within the field and presents findings at relevant meetings.
  • Takes on the role of mentoring graduate and/or undergraduate students.
  • Contributes proactively to the overall activities of both the research team and the Center.
  • Undertakes additional responsibilities as assigned by the Advisor.

The candidate will be working on the following specific tasks

  • Provision of a dataset focusing on Indoor Farms Plants Diseases, shared with an Industry Partner and integrated into the VRI database, enhancing accessibility and utilization across the agricultural community.
  • Development of a demonstration showcasing the application of robotics in monitoring crop diseases, utilizing cutting-edge technologies for real-time assessment and intervention.
  • Application of deep learning algorithms for Ripeness Monitoring and Disease Identification of Plants in Indoor Farms, offering a sophisticated and accurate method for early detection and analysis.
  • Provision of resources and benchmarks tailored for agricultural imagery-based pattern analysis, contributing to the advancement of methods for recognizing and understanding patterns in agricultural landscapes.
  • Exploration of efficient data sampling methods, data fusion techniques for multi/hyper-spectral image data, and the development of self, semi, and weakly supervised methods for greenhouse imagery, ensuring robust pattern recognition even in conditions of noise, sparsity, and imbalanced annotations.

Operational Responsibilities

Operational Responsibilities

Supervisory Responsibilities

NA

Should you require further assistance or if you face any issue with the online application, please feel to contact the Recruitment Team (recruitmentteam@ku.ac.ae ).

Get your free, confidential resume review.
or drag and drop a PDF, DOC, DOCX, ODT, or PAGES file up to 5MB.