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Post- Doctoral Associate in the Division of Engineering - Dr Tuka Alhanai

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الوصف الوظيفي

The Laboratory for ComputerHuman Intelligence (CHIlab in the Division of Engineering New York University Abu Dhabi is seeking a highly motivated Postdoctoral Associate to advance cuttingedge research in machine learning (ML). Our lab explores the intersection of artificial intelligence and humancomputer 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 humanAI collaboration and exploring systems tailored to dynamic humancentered environments. They may also work with diverse signal modalities including vision speech images and physiological signals.

Preferred Experience:
The lab highly values candidates with one or more of the following experiences:

HumanCentered Applications: Familiarity applying ML in areas like healthcare education neurorobotics 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 experience conducting usability studies and designing usercentric AI systems.

Assistive / Collaborative Robotics: Interest in developing robotic systems for rehabilitation assistive technology or neuroprosthetics leveraging machine learning to improve precision and adaptability in user interactions. Knowledge of deploying robots in shared workspaces focusing on safety cooperation and efficiency in humanrobot teams.

MultiModal 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: AIdriven 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.
Experience in one or more ML domains such as deep learning reinforcement learning or humancentered 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 toptier conferences (e.g. NeurIPS ICML CHI CVPR).

For consideration applicants need to submit a cover letter curriculum vitae with full publication list statement of research interests and two letters of reference all in PDF format. If you have any questions please email Prof. Tuka Alhanai at

The terms of employment are very competitive and include housing and educational subsidies for children. Applications will be accepted immediately and candidates will be considered until the position is filled.

About NYUAD:
NYU Abu Dhabi is a degreegranting research university with a fully integrated liberal arts and science undergraduate program in the Arts Sciences Social Sciences Humanities and Engineering. NYU Abu Dhabi NYU New York and NYU Shanghai form the backbone of NYUs global network university an interconnected network of portal campuses and academic centers across six continents that enable seamless international mobility of students and faculty in their pursuit of academic and scholarly activity. This global university represents a transformative shift in higher education one in which the intellectual and creative endeavors of academia are shaped and examined through an international and multicultural perspective. As a major intellectual hub at the crossroads of the Arab world NYUAD serves as a center for scholarly thought advanced research knowledge creation and sharing through its academic research and creative activities.

EOE/AA/Minorities/Females/Vet/Disabled/Sexual Orientation/Gender Identity Employer

UAE Nationals are encouraged to apply


Required Experience:

IC

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