Post-Doctoral Associate in the Division of Engineering

Description

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:

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

● Human-Centered Applications: Familiarity applying ML in areas like healthcare, education, neuro-robotics, and/or assistive technologies. Prior experience in physiological signal processing (, EMG, EEG, ECG) is an advantage. Familiarity with HCI principles and frameworks, in particular, experience conducting usability studies and designing user- centric AI systems.

● 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, cooperation, and efficiency in human-robot teams.

● 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 (, Python) and ML frameworks (, 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 (, NeurIPS, ICML, CHI, CVPR).