KU is seeking a highly motivated Research Engineer to work on designing, training and deploying of machine learning models for mobility and disconnection handling in routing protocols for mesh networks. The trained ML model needs to be able to predict disconnections with high accuracy ahead of their occurrence. Consequently, the routing protocol (QoS-OLSR for mesh networks) should be revised to take disconnection predictions into account to reduce disconnections while routing packets throughout the network. The candidate will be required to collect relevant data for the training process, train the ML model, integrate the final model into the protocol, and validate the new performance of the routing protocol.
As part of the project, the researcher will have access to state-of-the-art research equipment and facilities at the C2PS and will get an opportunity to work alongside researchers and graduate students from various backgrounds as part of a wider team.
Position Requirements
Experience in networks and routing protocols
Experience in different types of Machine learning.
Experience with using Linux and command-line tools
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
Qualifications
Candidate Profile
Essential Criteria
Bachelor\'s degree from a reputable university in ECE/CS or a related discipline
Experience in undertaking assigned research tasks and starting to manage own workload
Contributing to scientific papers and academic journal articles where possible acting as lead/ corresponding author
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
Bachelor\'s gained from and/or experience working in a top 200 QS or THE ranked University
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: Research Assistant Schedule: Regular Shift: Standard Job Type: Full-time
Times Higher Education
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