Post-Doctoral Associate in the Division of Engineering (Computer Engineering) - Dr. Tuka Alhanai
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Key skills for this role
About the Role
NYU Abu Dhabi's Laboratory for Computer-Human Intelligence seeks a Post-Doctoral Associate to advance research in machine learning, focusing on human-AI collaboration and multi-modal ML.
Key Skills for This Role
Responsibilities
- Engage in innovative research projects in ML, focusing on developing novel ML algorithms, enhancing human AI collaboration, and exploring systems tailored to dynamic, human centered environments
- Work with diverse signal modalities, including vision, speech, images, and physiological signals
Requirements
- PhD in Computer Science or related field, with no more than five years post receipt of the PhD
- Experience in one or more ML domains, such as deep learning, reinforcement learning, or human centered ML
- Proficiency in programming languages (e.g., Python) and ML frameworks (e.g., TensorFlow, PyTorch), with evidence in the form of public (Github) repository
- Excellent abilities in communication, teamwork, and mentorship
- Strong publication record in top tier conferences (e.g., NeurIPS, ICML, CHI, CVPR)
Full Job Posting
Position Overview
- The Laboratory for Computer Human Intelligence (CHI lab) in the Division of Engineering, New York University Abu Dhabi, is seeking a highly motivated Post Doctoral Associate to advance cutting edge research in machine learning (ML).
- Our lab explores the intersection of artificial intelligence, and human computer interaction, striving to create technologies that amplify human potential.
- The successful candidate will engage in innovative research projects in ML, focusing on developing novel ML algorithms, enhancing human AI collaboration, and exploring systems tailored to dynamic, human centered environments.
- They may also work with diverse signal modalities, including vision, speech, images, and physiological signals.
Preferred Experience
- Human Centered Applications: Familiarity applying ML in areas like healthcare, education, neuro robotics, and/or assistive technologies. Prior experience in physiological signal processing (e.g., EMG, EEG, ECG) is an advantage. Familiarity with HCI principles and frameworks, in particular, experienc
- Assistive / Collaborative Robotics: Interest in developing robotic systems for rehabilitation, assistive technology, or neuro prosthetics, leveraging machine learning to improve precision and adaptability in user interactions. Knowledge of deploying robots in shared workspaces, focusing on safety, c
- Multi Modal ML: Expertise in working with diverse data types, such as vision, speech, images, and physiological signals. Experience integrating multiple modalities to build robust AI systems is an advantage.
- Interdisciplinary Applications: Leveraging LLM / VLMs for interdisciplinary problems, such as: AI driven scientific discovery, automating hypothesis generation in finance / natural sciences / physical sciences, enhancing collaborative workflows in complex organizational settings.
Qualifications
- Applicants must have a PhD in Computer Science or related field, with no more than five years post receipt of the PhD.
- Experience in one or more ML domains, such as deep learning, reinforcement learning, or human centered ML.
- Proficiency in programming languages (e.g., Python) and ML frameworks (e.g., TensorFlow, PyTorch), with evidence in the form of public (Github) repository.
- Excellent abilities in communication, teamwork, and mentorship.
- Strong publication record in top tier conferences (e.g., NeurIPS, ICML, CHI, CVPR).
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