We’re Hiring: Part-Time Research Assistant (6 months, paid, UK-based only)

Location: Queen Mary University of London – Center for Multimodal AI & Center for Digital Music

Contract: 6 months

Eligibility: Must have the right to work in the UK and be currently UK-based (hybrid/remote work is possible)

We’re looking for a motivated and technically skilled Research Assistant to join our team at Queen Mary University of London (QMUL), in the School of Electronic Engineering and Computer Science. This role will support Dr. Iran R. Roman's research on multimodal AI.

About the Project

This project focuses on the development of AI models and datasets for multimodal machine perception. We’re building agents that combine data from multiple sensor modalities (such as vision, audio, and spatial metadata) to develop spatially aware representations of real-world scenes.

Responsibilities

• Assist in the development and evaluation of machine learning models that integrate vision, audio, and spatial cues
• Support the creation and management of large-scale synthetic and real-world multimodal datasets
• Help design and run experiments for model benchmarking and ablation studies
• Contribute to code development, documentation, analysis scripts, and preparation of publications

Qualifications

• A current MSc or PhD student, or a recent graduate, in Computer Science, Electrical Engineering, AI, or a related field
• Skilled in Python and familiar with machine learning libraries (e.g. PyTorch, TensorFlow)
• Comfortable working with multimodal data, or eager to learn (e.g., audio, video, 3D spatial data)
• Reliable, detail-oriented, and capable of working independently
• Excited by research at the intersection of machine learning and real-world sensing

Good to haves:

• Knowledge of signal processing theory, spatial audio, and acoustic simulation
• Prior experience with AI on edge devices
• Track record of scientific publications

We count with state-of-the-art compute to train large models. You will be working directly with an interdisciplinary team that is well connected with industry and publishes research at top-tier AI venues and journals.

To apply:

Send a short message and a 1-page resume to [email protected]

Applications will be screened as soon as they are received, and short-listed candidates will be interviewed on a rolling basis until the position is filled.