19 Epidemiology jobs in the United Arab Emirates

Epidemiology - Open Rank Faculty Positions

Mohamed bin Zayed University of Artificial Intelligence: Academic Appointments: School of Digital Public Health: Epidemiology

Abu Dhabi, UAE

Open Date: Jul 01, 2025

Deadline: Jun 30, 2026

Description:

Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) is seeking passionate and highly motivated faculty members in Epidemiology. Successful candidates will be responsible for delivering high-quality instruction, mentoring students, contributing to curriculum development, and engaging in interdisciplinary research. Faculty will have opportunities to collaborate with leading AI researchers, work on cutting-edge projects, and contribute to the university's growth as a hub for AI excellence.

Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) is looking for passionate and highly motivated Faculty. The successful candidates will be responsible for delivering high-quality instruction, mentoring students, contributing to curriculum development, and actively engaging in interdisciplinary research. Faculty members will also have the opportunity to collaborate with leading AI researchers, work on cutting-edge projects, and contribute to the university's growth as a hub for AI excellence.

The School of Public Health is at the forefront of research at the intersection of Genomics, Personalized Medicine, Epidemiology, and Artificial Intelligence (AI). A key initiative within the school is the Human Phenotype Project—a groundbreaking, large-scale longitudinal cohort and biobank designed to identify novel molecular markers with diagnostic, prognostic, and therapeutic value. This project involves deep profiling of participants through comprehensive data collection on medical history, lifestyle and nutritional habits, vitals, anthropometrics, blood tests, continuous glucose and sleep monitoring, and multi-omic molecular profiling, including genetics, transcriptomics, microbiomics, metabolomics, and immune system markers. The school leverages this data and advanced AI and medical, and computational models to generate insights into disease mechanisms, identifying novel biomarkers and developing state-of-the-art predictive models for disease onset and progression. These models are translated into personalized prevention strategies and innovative therapeutic interventions. Research areas of interest include, but not limited to:

• Computational and Systems Biology
• Medical and Health Informatics
• Personalized Medicine
• Foundation AI Models
• Multi-omics and Integrative Data Analysis
• Population-level Cohort and EHR Analysis
• Epidemiology
• Pandemics
• Biomedical Imaging

The Department of Epidemiology centers on understanding, tracking, and controlling pathogens at the population and individual levels. Researchers tackle a broad spectrum of topics, including pandemic modeling and forecasting, pathogen genomics, epidemiological big-data analytics, global health informatics, and vaccine development strategies. Drawing on the multi-omic insights from the Human Phenotype Project and other large-scale cohorts, this department seeks to identify risk factors and disease mechanisms, develop AI-driven surveillance tools, and design cutting-edge interventions to mitigate current and emerging infectious threats worldwide.

The School of Public Health is expanding and aims to grow to 60 faculty members over the next 3-4years.Faculty joining the department will have full access to unique datasets, including the Human Phenotype Project, enabling innovative research that pushes the boundaries of precision medicine. We invite candidates at all levels (Assistant, Associate and Full Professor) to apply.

AboutMBZUAI – A Global Leader in AI Research and Education

MBZUAI is the world’s first university dedicated exclusively to AI and is rapidly emerging as a global leader in the field. Since its establishment in 2019, MBZUAI has grown into a top-ranked AI institution, currently hosting 80+ world-class faculty and 330+ graduate students and ranking among the top 10 AI universities worldwide.

With ambitious plans to expand from 8 to over 20 AI departments and grow its faculty from 84 to 300 by 2030, MBZUAI is on a fast-track growth trajectory. By integrating academia, industry, and government collaboration, we are driving AI innovation to address real-world challenges in healthcare, sustainability, and beyond.

Why Join MBZUAI?

• Top-Tier Compensation: Competitive salaries aligned with leading global academic institutions
• Funding: MBZUAI empowers researchers with resources and academic freedom, fostering groundbreaking AI advancements in an environment of innovation and independent inquiry.
• Exceptional Benefits:
  • Comprehensivehealth & life insurance
  • Relocation supportfor international faculty
• State-of-the-Art Research Facilities: Cutting-edge AI labs and high-performance computing
• Live in Abu Dhabi:World’s safest city, year-round sunshine, rich culture, and modern amenities
• Industry & Government Collaborations: Work with top AI researchers, leading tech firms, and policymakers

This position requires a PhD in Computer Science or a closely related field. Candidates should have demonstrated excellence in conducting innovative and impactful research, and an interest in mentoring students.

To apply for this position, please submit the following items:

• Cover Letter
• Curriculum Vitae
• Statement of research vision and interests
• Statement of teaching interests, experience, and philosophy
• List of key publications for the last five years and Google Scholar H-Index
• Name and contact details for three referees (referees will be contacted during the recruitment process to upload their reference letter via Interfolio).

MBZUAI's mission includes fostering a diverse academic community. MBZUAI is an equal opportunity employer. The university actively recruits faculty from around the world, aiming to create an international and inclusive environment that reflects a wide range of cultures and perspectives.

Be a part of AI’s future – apply today at MBZUAI

This role supports strategic and operational decision-making across departments. It combines strong business acumen with technical proficiency in tools like Excel, SQL, Python, and Power BI.

• Data collection, cleaning, and analysis from various systems.
• Maintenance of regular performance dashboards for occupancy, revenue, collections, and expenses.
• Generation of actionable insights and data visualizations to support leadership in key decisions.
• Assistance with forecasting and scenario planning (e.g., revenue trends, cost optimization).
• Ad hoc analysis and research on market trends, competitors, and benchmarks.
• Collaboration with teams (Finance, Legal, IT, etc.) to understand business needs and validate data.
• Identification of inconsistencies or inefficiencies in data or internal workflows, and proposal of improvements.
• Support for automation of recurring reports using Excel, BI tools, SQL queries, or Python scripts.

• Bachelor's degree in a STEM field, Finance, Economics, Statistics, Business Analytics, or a related discipline.
• 2-4 years of experience in a business or data analysis role, preferably within real estate or operational functions.
• Familiarity with UAE real estate regulations is an advantage.
• Proficiency in Microsoft Excel (advanced level), SQL, and Python for data handling and automation.
• Experience with BI tools such as Power BI (or similar platforms).
• Ability to build dashboards, analyze KPIs, and explain findings to non-technical stakeholders.

• Full-time employment offers the opportunity to work with a dynamic team and contribute to the company's success.
• Employment Type: Full-time.
• Job Function: Business Development and Investment Management.

The Director of Data Analysis is responsible for collecting, processing, and analysing real estate data from various sources, with the aim of providing accurate, data-driven insights that support strategic decision-making in the real estate sector in United Arab Emirates. The role focuses on enhancing market transparency, developing sector-wide performance indicators, and supporting policy formulation and investment planning based on data.

Responsibilities

• Collecting and analyzing real estate data from multiple sources
• Processing and cleaning data to ensure its accuracy, consistency, and readiness for analysis
• Analyzing real estate data to extract and update the real estate index, which enhances market transparency
• Preparing reports and dashboards to support strategic decision-making
• Developing sector performance indicators (e.g., price indices, supply and demand, occupancy rates, etc.)
• Supporting policy development and investment planning by providing data-driven recommendations
• Contributing to real estate market studies and identifying market trends to support and update strategic urban development plans
• Collaborating with government entities and investors to provide transparent and accurate insights into the real estate market

Requirements

• Bachelor's degree in Economics, Statistics, Business Administration, Data Analysis, or a related field.
• 5 years of experience in data analysis or market research, with knowledge of the real estate market.
• Certifications in data analysis or economics are not required but are preferred
• Certifications in Data Analysis, such as RICS or CF

We are seeking a skilled professional to lead our data analysis team. As a Lead Data Analyst, you will be responsible for overseeing a team of analysts and collaborating with developers and stakeholders to ensure software meets business needs.

• Manage a team of data analysts
• Create data marts and data lakes using mappings
• Design user interfaces and dashboards for data visualization and interaction
• Test and validate software and data products for accuracy and reliability

• Bachelor's or master's degree in Computer Science, IT, or related field
• Experience with data processing and analysis using Data Bricks
• Expert-level proficiency in SQL, Python, SAS/R, Spark
• Deployment experience in databases, server/cloud environments (AWS, Azure), APIs, ODBCs, web apps

• Career Growth: Opportunities for professional development and advancement
• Performance-Based Compensation: Competitive pay linked to performance
• Inclusive Culture: Join a collaborative team that values innovation and every voice

This is an exciting opportunity to work with a talented team and contribute to our success.

Effective Business Decisions Using Data Analysis

ID 257

Course: Effective Business Decisions Using Data Analysis

This interactive, applications-driven 5-day course will highlight the added value that data analytics can offer a professional as a decision support tool in management decision making. It will show the use of data analytics to support strategic initiatives; to inform on policy information; and to direct operational decision making. The course will emphasize applications of data analytics in management practice; focus on the valid interpretation of data analytics findings; and create a clearer understanding of how to integrate quantitative reasoning into management decision making. Exposure to the discipline of data analytics will ultimately promote greater confidence in the use of evidence-based information to support management decision making.

• Discussions on applications of data analytics in management
• The importance of data in data analytics
• Applying data analytical methods through worked examples
• Focusing on management interpretation of statistical evidence
• How to integrate statistical thinking into the work domain

• Explain the scope and structure of data analytics.
• Apply a cross-section of useful data analytics.
• Interpret meaningfully and critically assess statistical evidence.
• Identify relevant applications of data analytics in practice.

• Professionals in management support roles
• Analysts who typically encounter data/analytical information regularly in their work environment
• Those who seek to derive greater decision-making value from data analytics

This course will utilise a variety of proven adult learning techniques to ensure maximum understanding, comprehension, and retention of the information presented. The daily workshops will be highly interactive and participative. This involves regular discussion of applications as well as hands-on exposure to data analytics techniques using Microsoft Excel. Delegates are strongly encouraged to bring and analyse data from their own work domain. This adds greater relevancy to the content. Emphasis is also placed on the valid interpretation of statistical evidence in a management context.

• Day One: Setting the Statistical Scene in Management
  • Introduction; The quantitative landscape in management
  • Thinking statistically about applications in management (identifying KPIs)
  • The integrative elements of data analytics
  • Data: The raw material of data analytics (types, quality, and data preparation)
  • Exploratory data analysis using Excel (pivot tables)
  • Using summary tables and visual displays to profile sample data
• Day Two: Evidence-based Observational Decision Making
  • Numeric descriptors to profile numeric sample data
  • Central and non-central location measures
  • Quantifying dispersion in sample data
  • Examine the distribution of numeric measures (skewness and bimodal)
  • Exploring relationships between numeric descriptors
  • Breakdown analysis of numeric measures
• Day Three: Statistical Decision Making – Drawing Inferences from Sample Data
  • The foundations of statistical inference
  • Quantifying uncertainty in data – the normal probability distribution
  • The importance of sampling in inferential analysis
  • Sampling methods (random-based sampling techniques)
  • Understanding the sampling distribution concept
  • Confidence interval estimation
• Day Four: Statistical Decision Making – Drawing Inferences from Hypotheses Testing
  • The rationale of hypotheses testing
  • The hypothesis testing process and types of errors
  • Single population tests (tests for a single mean)
  • Two independent population tests of means
  • Matched pairs test scenarios
  • Comparing means across multiple populations
• Day Five: Predictive Decision Making - Statistical Modeling and Data Mining
  • Exploiting statistical relationships to build prediction-based models
  • Model building using regression analysis
  • Model building process – the rationale and evaluation of regression models
  • Data mining overview – its evolution
  • Descriptive data mining – applications in management
  • Predictive (goal-directed) data mining – management applications

About the opportunity

The Growth Data Science Director will lead and accelerate growth strategies across marketing optimization, product initiatives (e.g., churn reduction), ecosystem plays, and ads revenue for talabat and Quick commerce. This role requires collaboration with product teams, senior marketing, and partner leadership to drive data-driven decisions and business growth.

What’s On Your Plate?

• Data Science: Define and execute data strategies aligned with company goals, leading cross-functional teams to develop innovative data-driven products and insights that impact business outcomes.
• Strategic Leadership and Business Acumen: Demonstrate strategic leadership, articulate vision, and incorporate emerging trends and technologies to add value.
• Collaboration and Influence: Work with stakeholders including executives, product managers, engineers, and external partners; represent the organization at industry events.
• Resource Management: Manage teams, budgets, and resources; prioritize projects; coach and mentor managers.
• Strategic Hiring and Talent Development: Recruit, develop career paths, and provide feedback to team members.
• Organizational Change Management: Lead change initiatives, communicate effectively, and manage resistance.

What you need to be successful

• 8-10+ years in data science, with leadership experience in managing teams or consulting.
• Ph.D. or Master’s in relevant fields such as computer science, statistics, or data science.
• Proven leadership in fostering high-performance teams and applying data science skills to create impactful products and insights.
• Deep knowledge of statistics, causality, experimentation, and modeling.
• Business acumen with experience in quantifying impact through data initiatives.
• Strategic thinking and ability to develop data-driven roadmaps aligned with organizational goals.

Who we are

Since 2004, talabat has been Kuwait’s leading on-demand food and Q-commerce app, serving eight countries. We leverage technology to simplify life, optimize operations, and provide earning opportunities. We foster a high-performance culture, value authenticity, and are proud of our awards and diverse team of over 6,000 Talabaty committed to making a difference.

Requisition Number: 23219BR

Description:

At Stantec, we approach every project as a partnership, because our work creates a lasting impact on our clients’ communities. We believe that when smart, passionate, creative people come together, real possibilities are within reach.

Stantec is currently looking for a Public Health Engineer to join our dynamic team in Dubai.

1. Perform various Public Health, Plumbing, and Fire protection Engineering tasks, including sizing domestic water and drainage piping requirements, reviewing different plumbing design approaches, sizing equipment and tanks, and sizing water heating systems and fire protection systems.
2. Coordinate the engineering work between other members of the Building Services and Architectural teams.
3. Work under the direct supervision of the Senior Engineer and be accountable for specific discipline designer activities assigned.

1. Must be a Mechanical Engineer with a recognized degree from a nationally accredited engineering program.
2. 8-10 years of minimum experience working within an International Design Firm, focusing on Building Services Design.
3. Experience in hospital or healthcare projects is essential.
4. Proven PHE Design experience.
5. Ideally experienced with HX2 IES or Hevacomp.
6. Ideally, MASHRAE or MCIBSE certified.
7. Experience with Revit, AutoCAD, and proper draughting methods and techniques.
8. Understanding of standard industry software.
9. Strong written and verbal communication skills.
10. Working knowledge of computer programs and web-based applications including Microsoft Outlook, Word, and Excel.
11. Logical and analytical thinking.
12. Flexibility and adaptability.
13. Ability to work in a team-oriented environment.

Work Location(s): United Arab Emirates-Dubai

Employment Type: Full-Time

Job Type: Regular

Job Category: Mechanical Engineering