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Junior Research Scientist in the Division of Engineering (Electrical and Computer Engineering) - Dr. Farah Shamout

New York University Abu Dhabi
Abu Dhabi, UAE
Full Time
Entry
Onsite
1 months ago
Machine LearningPythonPyTorchTensorFlowMulti modal LearningFoundation Models
Free

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Job Overview

  • The Clinical Artificial Intelligence Lab at NYU Abu Dhabi seeks to improve patient care by developing new machine learning methodologies for healthcare applications.
  • We use large real world complex datasets, including electronic health records and medical images, for patient diagnostics and prognostics.

Skills

  • Multi modal learning
  • Foundation models, including large language models
  • Agentic AI
  • Multi agent AI systems
  • Transfer learning
  • Self supervised learning
  • Federated learning

Key Responsibilities Research

  • Support the supervisor in developing and implementing the research agenda.
  • Conduct high quality and innovative research primarily focused on ML for healthcare.
  • Design and implement experiments to compare proposed work with SOTA baselines.
  • Publish research findings in high impact journals and conferences.
  • Communicate and present research findings at international academic gatherings.
  • Create, maintain, and document high quality research code for reproducibility.
  • Maintain good practice in managing and accessing sensitive medical datasets.
  • Collaborate with scientists within the NYU Global Network and in Abu Dhabi.

Minimum Qualifications

  • Currently has or is in the process of completing a bachelor’s or master’s degree from a recognized institution.
  • Bachelor’s/Master’s degree in computer science, mathematics, computer engineering, or relevant technical field.
  • Demonstrable research experience involving data pre processing and preparation for machine learning models.
  • Demonstrable research experience in conducting experiments for training and evaluating deep neural networks.
  • Knowledge of multi modal learning, transfer learning, transformers, or self supervised learning.
  • Experience in dealing with large medical datasets (e.g., electronic health records data or medical images).
  • Ability to use high performance computing cluster.
  • Proficient programming experience in Python and libraries (e.g., Pytorch, TensorFlow).
  • Experience in maintaining high quality code on Github.
  • Experience in running and managing experiments using GPUs.
  • Ability to visualize experimental results and learning curves.
  • Effective inter personal and team building skills.

Preferred Qualifications

  • Bachelor’s/Master’s thesis conducted in the area of machine learning for healthcare and related topics.
  • First author peer reviewed published papers (or under review).
  • Evidence of leadership and service activities in the academic domain.

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