General Details

Position Code: Post Doctoral Fellow.8800161
Position Type: Project Based (Fixed Term)
Position Duration: 01/11/2023 to 30/11/2024
Position Title: Post-Doctoral Fellow
Project Title: Predictive modelling of a turbulent airwake behind a ship\'s superstructure using Machine Learning
Project Supervisor: Vladimir Parezanovic, Assistant Professor,
Academic Department: Aerospace Engineering
Technical Keywords: Ship Airwakes, Turbulent Flows, Wind Tunnel Experiments, Separated Flows, Large Eddy Simulations, Remote Sensing, Machine Learning

About Khalifa University

Khalifa University is ranked 181st in the QS World University Rankings 2023, and the top University in the UAE, with a range of research and academic programs designed to address the entire range of strategic, scientific and industrial challenges facing our rapidly evolving world.

Its world-class faculty and state-of-the-art research facilities provide an unparalleled learning experience to students from the UAE and around the world. Our research and academic activities cover a broad range of disciplines in engineering, science and medicine through our three colleges.

Khalifa University\'s research relates to key focus sectors of relevance to the UAE\'s strategic economic growth and the technology platforms that serve as foundations for these sectors. The University\'s research priorities are addressed in two categories \xe2\x80\x9cverticals\xe2\x80\x9d and \xe2\x80\x9chorizontals\xe2\x80\x9d which jointly cover specific industry and sector needs, technical platforms and expertise.

KU\'s focus sectors are Clean and Renewable Energy, Hydrocarbon Exploration and Production, Water and Environment, Healthcare, Aerospace, and Supply Chain and Logistics. Research in these sectors is enhanced by our research platforms of Robotics, AI and Data Science, Information and Communication Technologies, and Advanced Materials and Manufacturing as well as Fundamental Sciences.

Position Overview

KU is seeking a highly motivated Post-doctoral Fellow to work on predicting the behavior and properties of the turbulent air wake behind a ship\'s superstructure as a fundamental problem in fluid mechanics.

This study can potentially have a wide-ranging impact on the improvement of helicopter operation envelopes on existing maritime (ship-helo) systems, and major considerations in new ship designs. Based on the wake state data from the wind tunnel experiments and numerical simulations, a predictive model of the air wake behavior will be created using advanced Machine Learning methods, such as Genetic Programming, Variable Neighborhood Search, and others.

The post-doctoral fellow will lead the effort in obtaining high-fidelity data on the airwake from wind tunnel experiments and/or CFD and will be responsible for analyzing the data and creating a reduced-order-model (ROM) of the flow, which will be suitable for the prediction of the flow by a sparse sensor array.

As part of the project, the researcher will have access to state-of-the-art research equipment and facilities at the new KU Low-Speed Wind tunnel facility and will get an opportunity to work alongside researchers and graduate students from various backgrounds as part of a wider team.

Position Requirements

• Participates in scientific research as a professionally responsible member of the research team, participates in problem exploration, and definition, planning of the approach and sequence of steps, execution of experiments and/or CFD simulations, interpretation of findings, documentation and reporting of results and progress, maintenance of research records and compliance to all established policies and procedures;
• Regularly meets with the Advisor to apprise the Advisor of the research results, for the development and troubleshooting of techniques, to provide direction and focus to the research, to air concerns and conflicts, and to express mutual expectations;
• Publishes research results in journals appropriate to the field in a timely manner, may present findings at meetings;
• Participates in writing grant applications and proposals that pertain to the research;
• Contributes to the overall activities of the research team and the department, as required;
• Undertakes a limited amount of teaching in relation to subject area and mentors graduate students and/or undergraduates under the supervision of the Advisor;
• Adheres to the University\'s information security and confidentiality policies and procedures, and reports breaches or other security risks accordingly;
• Perform any other tasks assigned by the Line Manager

Qualifications

Candidate Profile

Essential Criteria

• PhD from a reputable university in Aerospace Engineering, Fluid Mechanics or related discipline.
• Experience writing scientific and review papers;
• A willingness to contribute to a collaborative and supportive team culture
• Excellent English language communication skills (verbal and written)
• Ability to work both independently and as part of a team
• The proven ability to work on multiple tasks with competing demands and deadlines.
• Ability to train and mentor students and support fellow researchers
• Highly developed reasoning and problem-solving skills

Desired Criteria

• PhD gained from a top 200 QS or THE ranked University
• At least 1 year of relevant experience as a Post-doctoral researcher in academia or in industry.
• High impact first-author publications in top 10% journals in the relevant field
• Solid experience with wind tunnel testing and/or CFD for turbulent flows
• Experience in modelling of dynamical systems, turbulent flows, optimization methods, machine learning methods, etc.

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

Primary Location: Abu Dhabi UAE
Job: Post Doctoral Fellow
Schedule: Regular
Shift: Standard
Job Type: Full-time

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