Postdoctoral Research Fellow in Natural Water Systems

American University of Sharjah; Sharjah; On-site; AED 120,000 - 180,000; Full time

Job summary

A leading academic institution in the UAE seeks a Postdoctoral Research Fellow in Natural Water Systems. The role involves conducting research on monitoring and management of aquatic ecosystems. Candidates should have a PhD in relevant fields and skills in chemical analysis and AI for environmental data modeling. The position offers opportunities for mentorship and collaboration in a multidisciplinary setting.

Qualifications

• PhD in relevant fields is mandatory.
• Experience with chemical analysis and environmental data modeling expected.
• Strong initiative and problem-solving skills are crucial.

Responsibilities

• Utilize advanced instruments for real-time water quality assessment.
• Conduct analysis of water and sediments.
• Develop predictive models using AI and machine learning.

Skills

Chemical analysis techniques (ICP-MS, GC-MS, FTIR, SEM, HPLC)

AI/ML tools for environmental data modeling

Water quality monitoring

Contaminant detection

Biodiversity assessment

Analytical chemistry

Ecological modeling

Environmental data science

Laboratory equipment familiarity

Strong written and verbal communication in English

Education

PhD in Environmental Science, Environmental Engineering, Chemistry, Water Resources, or related fields

Tools

Advanced water quality sensors

Job description

Post:

Postdoctoral Research Fellow in Natural Water Systems

Position Summary

To conduct multidisciplinary research in monitoring, modeling, and sustainable management of natural water systems. The fellow will support advanced environmental monitoring, pollutant assessment, and the development of AI-enhanced frameworks to understand water quality, biodiversity, climate impacts, and pollution control in the UAE’s aquatic ecosystems.

Job Responsibilities

• Utilize advanced water quality sensors instruments for real-time assessment.
• Conduct elemental and chemical analysis of water and sediments (e.g., ICP-OES, GC-MS, FTIR, SEM, etc.).
• Apply AI, machine learning, and remote sensing to automate data analysis and develop predictive models.
• Investigate microplastics, pharmaceuticals, and persistent pollutants in aquatic environments.
• Conduct biodiversity monitoring using eDNA and biomarkers.
• Publish research outcomes in leading peer-reviewed journals.
• Contribute to writing technical reports and grant deliverables.
• Mentor and collaborate with graduate students and junior researchers.
• Participate in project meetings and communicate findings to stakeholders.
• Participate in organizing conferences and workshops.

Qualifications And Skills Required

• PhD in Environmental Science, Environmental Engineering, Chemistry, Water Resources, or related fields.
• Skilled in chemical analysis techniques (ICP-MS, GC-MS, FTIR, SEM, HPLC, etc.).
• Familiarity with AI/ML tools for environmental data modeling.
• Experience in water quality monitoring, contaminant detection, and biodiversity assessment.
• Proficiency in analytical chemistry, ecological modeling, and environmental data science.
• Understanding of aquatic ecosystems, pollutant pathways, and sustainability principles.
• Familiarity with laboratory equipment.
• Strong written and verbal communication skills in English.
• High degree of independence, initiative, and problem-solving skills.

Preferred Qualifications And Skills

• Interdisciplinary background with experience in AI, remote sensing, or ecological monitoring.
• Prior research involvement in projects involving climate change modeling or aquatic ecosystem restoration.
• Experience in supervising or mentoring graduate-level researchers

How To Apply

• Interested applicants should fill out this form.
• AUS alumni are encouraged to apply. Applicants who do not meet specified requirements will not be shortlisted. Only shortlisted candidates will be contacted.
• AUS is an equal opportunity employer. We adhere to a policy of making employment decisions without regard to race, color, age, gender, religion, national origin, disability or marital status. Opportunities for employment are based solely upon one’s qualifications.