Postdoctoral Associate in Human-Centered Machine Learning
Join NYU Abu Dhabi’s CHI-lab to develop next-generation AI systems that enhance human-AI collaboration through multimodal learning and assistive technologies.
Best for:Best for postdoctoral researchers with a PhD in Computer Science or related fields, expertise in human-centered ML, and experience in multimodal data processing or assistive technologies.
Overview
This postdoctoral position at the Laboratory for Computer-Human Intelligence (CHI-lab) at New York University Abu Dhabi focuses on advancing machine learning (ML) at the intersection of artificial intelligence and human-computer interaction. The successful candidate will contribute to cutting-edge research in human-centered AI, including novel ML algorithms, human-AI collaboration systems, and applications leveraging diverse signal modalities like vision, speech, and physiological data. The role emphasizes interdisciplinary collaboration, with opportunities to work on assistive robotics, neuro-prosthetics, and LLM/VLM applications across scientific and organizational domains. The lab seeks researchers with a strong publication record and expertise in deep learning, reinforcement learning, or human-centered AI to drive impactful, user-centric innovations.
What you'll do
- Develop novel machine learning algorithms tailored for human-centered applications, including healthcare, education, and assistive technologies.
- Design and implement AI systems that integrate multimodal data (e.g., vision, speech, physiological signals) to enhance human-AI collaboration.
- Conduct research on assistive and collaborative robotics, focusing on precision, adaptability, and user interaction in dynamic environments.
- Collaborate on interdisciplinary projects leveraging LLMs and VLMs for scientific discovery, hypothesis generation, or organizational workflow optimization.
- Conduct usability studies and design user-centric AI systems informed by human-computer interaction (HCI) principles.
- Publish research findings in top-tier conferences and journals, contributing to the lab’s reputation for innovative, impactful work.
- Mentor junior researchers or students and contribute to the lab’s collaborative and interdisciplinary research culture.
Requirements
Degree required: PhD in Computer Science or a closely related field, with no more than five years of post-PhD experience.
Language: English; proficiency required for research communication and collaboration.
Instruction: English
Publications: Strong publication record in top-tier conferences (e.g., NeurIPS, ICML, CHI, CVPR).
- Proven expertise in machine learning domains such as deep learning, reinforcement learning, or human-centered ML.
- Strong programming proficiency in Python and experience with ML frameworks like TensorFlow or PyTorch.
- Publicly available evidence of research contributions (e.g., GitHub repositories).
- Experience with physiological signal processing (e.g., EEG, EMG, ECG) is highly valued.
- Excellent communication, teamwork, and mentorship skills.
- Strong publication record in top-tier conferences (e.g., NeurIPS, ICML, CHI, CVPR).
- PhD in Computer Science or a related field.
- No more than five years of post-PhD experience.
- No explicit nationality or residency restrictions, though Emirati candidates are encouraged to apply.
Funding & terms
How to apply
Deadline: 2026-10-28
Applicants must submit a cover letter, curriculum vitae with a full publication list, transcript, statement of research interests, and two letters of reference, all in PDF format. Applications should be sent via email to the specified contact.
- Cover letter
- Curriculum vitae with full publication list
- Transcript
- Statement of research interests
- Two letters of reference
Contact
Prof. Tuka Alhanai· Supervisor
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