Research Engineer in the Division of Engineering ComputerEngineering - Abu Dhabi, United Arab Emirates - New York University Abu Dhabi

Description

• Support the supervisor indeveloping and implementing the researchagenda;
• Conduct high-quality and innovativeresearch primarily focused on ML methodology development forhealthcare;
• Reproduce results of thestate-of-the-art (SOTA) methods;
• Design andimplement experiments to compare proposed work with SOTAbaselines;
• Contribute to the preparation ofmanuscripts for publication in high-impact journals andconferences;
• Create, maintain, and documenthigh-quality research code forreproducibility;
• Maintain good practice inmanaging and accessing sensitive medicaldatasets;
• And collaborate with scientistswithin the NYU Global Network and in AbuDhabi.

MinimumQualifications

• Currentlyhas or is in the process of completing a Master's degreeor equivalent terminal degree from a recognizedinstitution
• Master's degree incomputer science, mathematics, computer engineering, or relevanttechnical field
• Demonstrable researchexperience involving data pre-processing and preparation formachine learning models
• Demonstrable researchexperience in conducting experiments for training and evaluatingdeep neural networks
• Ability to use highperformance computing cluster
• Proficientprogramming experience in Python and libraries (e.g., Pytorch,TensorFlow) with several years ofpractice
• Experience in maintaining high-qualitycode on Github
• Ability to visualizeexperimental results and learningcurves
• Effective inter-personal andteam-building skills
• Self-motivated with anability to work independently and in a team to get the workdone
• Excellent communication skills (oral andwritten communication)
• Willingness to learn andconfront newchallenges

PreferredQualifications

• Master'sthesis conducted in the area of machine learning for healthcare andrelated topics
• First-author peer-reviewedpublished papers (or under review)
• Knowledge ofmulti-modal learning, transfer learning, graph neural networks,transformers, or self-supervisedlearning
• Experience in dealing with largemedical datasets (e.g., electronic health records data or medicalimages)