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\xe2\x80\x99s research relates to key focus sectors of relevance to the UAE\xe2\x80\x99s strategic economic growth and the technology platforms that serve as foundations for these sectors. The University\xe2\x80\x99s research priorities are addressed in two categories \xe2\x80\x94 \xe2\x80\x9cverticals\xe2\x80\x9d and \xe2\x80\x9chorizontals\xe2\x80\x9d \xe2\x80\x94 which jointly cover specific industry and sector needs, technical platforms and expertise.
KU\xe2\x80\x99s 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 Research Assistant to work on two-dimensional optimal stopping problems arising in mathematical finance. The examples of such problems include real options problems (e.g., option to switch to idle state, option to wait to invest in risky projects, options to select the best of several technologies); optimal capital structure problems (i.e., optimal default problem for equity holders, valuation of equity and debt contracts, maximization of total firm value);
valuation of recently proposed mortgage contracts taking into the account prepayment and default options. The candidate will develop and implement efficient numerical schemes to tackle these problems. These schemes will be based on the combination of the following methods: Monte-Carlo simulations, free boundary and fixed boundary PDEs, integral equations, neural networks.
Qualifications
Position Overview
KU is seeking a highly motivated Research Assistant to work on two-dimensional optimal stopping problems arising in mathematical finance. The examples of such problems include real options problems (e.g., option to switch to idle state, option to wait to invest in risky projects, options to select the best of several technologies); optimal capital structure problems (i.e., optimal default problem for equity holders, valuation of equity and debt contracts, maximization of total firm value);
valuation of recently proposed mortgage contracts taking into the account prepayment and default options. The candidate will develop and implement efficient numerical schemes to tackle these problems. These schemes will be based on the combination of the following methods: Monte-Carlo simulations, free boundary and fixed boundary PDEs, integral equations, neural networks.
Position Requirements
Strong background in Mathematics, machine learning and numerical methods
Adhere to the University\'s information security and confidentiality policies and procedures, and report breaches or other security risks accordingly
Perform any other tasks assigned by the Line Manager
Candidate Profile
Essential Criteria
Bachelors from a reputable university in Mathematics or related discipline
Experience of undertaking assigned research tasks and contributing to academic outputs
A willingness to contribute to a collaborative and supportive team culture
Excellent English language communication skills (verbal and written)
Ability to function as part of a team working on multiple tasks with competing demands and deadlines
Well-developed reasoning and problem-solving skills
Desired Criteria
Bachelors gained from and/or experience working in a top 200 QS or THE ranked University
At least 1 year of relevant experience as a researcher in academia or in industry
Experience contributing to high impact publications in top 10% journals in the relevant field