Researcher Jobs in Qatar

Responsibilities<br><br>Own and lead multiple physiology and exercise research initiatives for WHOOP Labs Doha as part of multi-site data collection efforts. Execute study sessions with participants and provide in-the-moment movement coaching and support as needed to ensure successful protocol compliance. Collaborate closely with the WHOOP Labs Boston team to understand project goals, technical constraints, and protocol nuances. Own localization of protocols for execution in Doha including any required changes to activities, session structure, or sample. Develop and maintain clear research plans, workflows, and deliverables, adapting to evolving priorities and constraints. Manage research programs and dependencies using project management tools, ensuring visibility, accountability, and on-time delivery. Collaborate with other members of the WHOOP Labs Doha team such as Recruitment, Lab Management, and other Researchers to ensure successful end-to-end study delivery. Provide best-in-class customer service to WHOOP Labs Doha visitors. Communicate research updates and findings clearly and confidently, translating complex insights into recommendations that inform decision-making.<br><br>Qualifications<br><br>Bachelor’s degree or professional experience in a relevant field such as research & development, human subjects research, engineering, physiology, or a related discipline.2+ years of experience conducting research in a physiology, performance science, or similar environment. Experience conducting AMR, VO2 Max, strength assessment, or similar protocols desired. Experience applying research methods relevant to physiology such as coaching on specific exercises / movements, leading group activities, or sports coaching. Strong project and program management skills, with comfort using tools such as Jira or similar planning frameworks. Ability to manage multiple concurrent research initiatives and operate effectively in ambiguous, fast-paced environments. Excitement to work in a high-energy, fast-paced startup environment Fluency in verbal and written English, WHOOP’s working language Comfort communicating with Doha locals in English and Arabic<br><br>Interested in the role, but don’t meet every qualification? We encourage you to still apply! At WHOOP, we believe there is much more to a candidate than what is written on paper, and we value character as much as experience. As we continue to build a diverse and inclusive environment, we encourage anyone who is interested in this role to apply.<br><br>WHOOP is an Equal Opportunity Employer and participates in E-verify to determine employment eligibility. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.<br><br>The WHOOP compensation philosophy is designed to attract, motivate, and retain exceptional talent by offering competitive base salaries, meaningful equity, and consistent pay practices that reflect our mission and core values.<br><br>At WHOOP, we view total compensation as the combination of base salary, equity, and benefits, with equity serving as a key differentiator that aligns our employees with the long-term success of the company and allows every member of our corporate team to own part of WHOOP and share in the company’s long-term growth and success.<br><br>In addition to the base salary, the successful candidate will also receive benefits and a generous equity package.<br><br>These ranges may be modified in the future to reflect evolving market conditions and organizational needs. While most offers will typically fall toward the starting point of the range, total compensation will depend on the candidate’s specific qualifications, expertise, and alignment with the role’s requirements.

Overview<br><br>University of Doha for Science and Technology (UDST), officially established by Emiri Decision No. 13 of 2022, is Qatar’s first national applied university and the country’s premier destination for academic, technical, and professional education. With more than 9,000 students and 700 staff, UDST offers over 70 bachelor’s, master’s, diploma, and certificate programs across its five colleges: Business, Computing & Information Technology, Engineering & Technology, Health Sciences, and General Education. In addition, UDST houses specialized training centers that serve both individuals and industry<br><br>UDST is recognized for its student-centered learning, cutting-edge facilities, and applied, experiential approach. Our world-class faculty and researchers leverage innovative learning technologies and foster partnerships with global institutions to develop highly skilled graduates who contribute directly to Qatar’s knowledge-based economy and support the goals of Qatar National Vision 2030. As a growing hub for research and innovation, UDST is home to advanced projects that bridge academia and industry.<br><br>UDST Center of Excellence - Artificial Intelligence and Innovation is dedicated to advancing cutting-edge AI research and developing practical solutions that tackles real-world challenges. Our mission is to drive scientific progress and technological innovation in intelligent systems, contributing to Qatar's transition to a knowledge-based economy in line with Qatar National Vision 2030.<br><br>We are seeking an outstanding Postdoctoral Researcher to join our team at the Center of Excellence in Artificial Intelligence and Innovation. This role focuses on conducting applied research in machine learning, federated learning, and explainable AI (XAI) with real-world applications in healthcare, energy, and smart infrastructure. You will develop privacy-preserving machine learning systems, create interpretable AI solutions, and deploy models on edge and cloud platforms. This is an excellent opportunity to advance trustworthy AI research while contributing to Qatar’s innovation priorities and digital transformation.<br><br>Responsibilities<br><br>Key Responsibilities<br><br>Conduct applied research in machine learning, federated learning, and explainable AI across domains such as healthcare, energy, and smart infrastructure Develop privacy-preserving machine learning systems and interpretable AI solutions that ensure transparency and trust Deploy machine learning models on edge and cloud platforms, ensuring robustness and scalability Publish research findings in top-tier peer-reviewed conferences and journals Lead and contribute to high-impact research projects aligned with the Center's priorities Ensure reproducibility and documentation of research through best practices in code and data management Integrate XAI techniques to ensure AI solutions meet ethical standards and domain-specific requirements Collaborate with internal and external stakeholders on interdisciplinary research initiatives Contribute to research proposals and external funding applications to support the Center's growth Mentor junior researchers, graduate students, and research assistants<br><br>Qualifications<br><br>Required Qualifications<br><br>PhD in Computer Science, Artificial Intelligence, Machine Learning, or a closely related field Demonstrated research experience in machine learning, with focus on federated learning, explainable AI, or privacy-preserving MLStrong publication record in peer-reviewed journals and top-tier AI/ML conferences (e.g., Neur IPS, ICML, ICLR, AAAI, CVPR, KDD) Expertise in deep learning frameworks (PyTorch, Tensor Flow, Keras) and classical ML tools (scikit-learn, XGBoost) Strong background in machine learning, federated learning, or explainable AIExperience with evaluating AI models, benchmark design, and assessment methodologies Experience with explainable AI libraries (e.g., SHAP, LIME, Captum) and interpretability techniques Experience with federated learning frameworks (e.g., Flower, Tensor Flow Federated) or privacy-preserving MLProven ability to conduct independent research and contribute to collaborative research teams Excellent analytical, problem-solving, and communication skills, including research presentations and technical writing Proficiency with version control systems (Git) and reproducible research practices Experience with computational resources and high-performance computing environments Fluency in written and spoken English<br><br>Preferred Qualifications How to Apply<br><br>Experience applying ML to healthcare, energy, or smart infrastructure domains Familiarity with AI safety, alignment, fairness, bias detection, or responsible AI research Experience with cloud and edge deployment platforms (e.g., AWS Sage Maker, Azure ML, Docker, Kubernetes) Knowledge of MLOps practices, CI/CD pipelines, and model deployment Experience with model monitoring, drift detection, and retraining strategies Experience with data engineering and preprocessing tools (e.g., Spark, Airflow, data versioning) Understanding of human-AI interaction and user-centered AI design Familiarity with domain-specific toolkits (e.g., MONAI for medical imaging, FHIR for healthcare data) Track record of research impact (citations, h-index, awards) Experience with interdisciplinary research or industry collaborations Previous postdoctoral or industrial research experience Experience with grant writing and research funding applications Contributions to open-source AI projects or frameworks Arabic language skills What We Offer Competitive salary and comprehensive benefits package Opportunity to conduct applied research in ML, federated learning, and explainable AI with real-world impact in healthcare and energy Collaborative and dynamic work environment with cutting-edge technology Access to state-of-the-art facilities and computational resources through strategic partnerships Professional development opportunities, international collaborations, and conference participation<br>Interested Candidates Should Submit The Following Documents<br><br>Updated CV/Resume Cover letter highlighting research experience, interests, and motivation List of publications and research statement (required) Contact information for two professional references<br><br>Application Deadline: 31st March 2026<br><br>UDST is an equal opportunity employer committed to building a diverse and inclusive workforce. We welcome applications from all qualified candidates regardless of race, color, religion, gender, national origin, age, disability, or veteran status.

Overview<br><br>University of Doha for Science and Technology (UDST), officially established by Emiri Decision No. 13 of 2022, is Qatar’s first national applied university and the country’s premier destination for academic, technical, and professional education. With more than 9,000 students and 700 staff, UDST offers over 70 bachelor’s, master’s, diploma, and certificate programs across its five colleges: Business, Computing & Information Technology, Engineering & Technology, Health Sciences, and General Education. In addition, UDST houses specialized training centers that serve both individuals and industry<br><br>UDST is recognized for its student-centered learning, cutting-edge facilities, and applied, experiential approach. Our world-class faculty and researchers leverage innovative learning technologies and foster partnerships with global institutions to develop highly skilled graduates who contribute directly to Qatar’s knowledge-based economy and support the goals of Qatar National Vision 2030. As a growing hub for research and innovation, UDST is home to advanced projects that bridge academia and industry.<br><br>UDST Center of Excellence - Artificial Intelligence and Innovation is dedicated to advancing cutting-edge AI research and developing practical solutions that tackles real-world challenges. Our mission is to drive scientific progress and technological innovation in intelligent systems, contributing to Qatar's transition to a knowledge-based economy in line with Qatar National Vision 2030.<br><br>We are seeking an outstanding Postdoctoral Researcher to join our team at the Center of Excellence in Artificial Intelligence and Innovation. This role focuses on conducting applied research in machine learning, federated learning, and explainable AI (XAI) with real-world applications in healthcare, energy, and smart infrastructure. You will develop privacy-preserving machine learning systems, create interpretable AI solutions, and deploy models on edge and cloud platforms. This is an excellent opportunity to advance trustworthy AI research while contributing to Qatar’s innovation priorities and digital transformation.<br><br>Responsibilities<br><br>Key Responsibilities<br><br>Conduct applied research in machine learning, federated learning, and explainable AI across domains such as healthcare, energy, and smart infrastructure Develop privacy-preserving machine learning systems and interpretable AI solutions that ensure transparency and trust Deploy machine learning models on edge and cloud platforms, ensuring robustness and scalability Publish research findings in top-tier peer-reviewed conferences and journals Lead and contribute to high-impact research projects aligned with the Center's priorities Ensure reproducibility and documentation of research through best practices in code and data management Integrate XAI techniques to ensure AI solutions meet ethical standards and domain-specific requirements Collaborate with internal and external stakeholders on interdisciplinary research initiatives Contribute to research proposals and external funding applications to support the Center's growth Mentor junior researchers, graduate students, and research assistants<br><br>Qualifications<br><br>Required Qualifications<br><br>PhD in Computer Science, Artificial Intelligence, Machine Learning, or a closely related field Demonstrated research experience in machine learning, with focus on federated learning, explainable AI, or privacy-preserving MLStrong publication record in peer-reviewed journals and top-tier AI/ML conferences (e.g., Neur IPS, ICML, ICLR, AAAI, CVPR, KDD) Expertise in deep learning frameworks (PyTorch, Tensor Flow, Keras) and classical ML tools (scikit-learn, XGBoost) Strong background in machine learning, federated learning, or explainable AIExperience with evaluating AI models, benchmark design, and assessment methodologies Experience with explainable AI libraries (e.g., SHAP, LIME, Captum) and interpretability techniques Experience with federated learning frameworks (e.g., Flower, Tensor Flow Federated) or privacy-preserving MLProven ability to conduct independent research and contribute to collaborative research teams Excellent analytical, problem-solving, and communication skills, including research presentations and technical writing Proficiency with version control systems (Git) and reproducible research practices Experience with computational resources and high-performance computing environments Fluency in written and spoken English<br><br>Preferred Qualifications How to Apply<br><br>Experience applying ML to healthcare, energy, or smart infrastructure domains Familiarity with AI safety, alignment, fairness, bias detection, or responsible AI research Experience with cloud and edge deployment platforms (e.g., AWS Sage Maker, Azure ML, Docker, Kubernetes) Knowledge of MLOps practices, CI/CD pipelines, and model deployment Experience with model monitoring, drift detection, and retraining strategies Experience with data engineering and preprocessing tools (e.g., Spark, Airflow, data versioning) Understanding of human-AI interaction and user-centered AI design Familiarity with domain-specific toolkits (e.g., MONAI for medical imaging, FHIR for healthcare data) Track record of research impact (citations, h-index, awards) Experience with interdisciplinary research or industry collaborations Previous postdoctoral or industrial research experience Experience with grant writing and research funding applications Contributions to open-source AI projects or frameworks Arabic language skills What We Offer Competitive salary and comprehensive benefits package Opportunity to conduct applied research in ML, federated learning, and explainable AI with real-world impact in healthcare and energy Collaborative and dynamic work environment with cutting-edge technology Access to state-of-the-art facilities and computational resources through strategic partnerships Professional development opportunities, international collaborations, and conference participation<br>Interested Candidates Should Submit The Following Documents<br><br>Updated CV/Resume Cover letter highlighting research experience, interests, and motivation List of publications and research statement (required) Contact information for two professional references<br><br>Application Deadline: 31st March 2026<br><br>UDST is an equal opportunity employer committed to building a diverse and inclusive workforce. We welcome applications from all qualified candidates regardless of race, color, religion, gender, national origin, age, disability, or veteran status.