We are seeking a motivated University of Sheffield student to support an innovative research project developing CognoMND™, an AI-powered tool for remote cognitive screening in Motor Neuron Disease using speech and language. The project sits within Neuroscience, Linguistics and Computer Science and involves analysing speech samples collected from cognitive tasks. The role will appeal to students interested in phonetics, cognition, digital health, or clinically relevant research.
Pay Rate: £17.58 per hour + holiday pay entitlement
Location: Remote working
Hours per week: Approx. 4–6 hours per week
Total hours: 80 hours
Duration: December 2025 - April 2026
Job Description:
The Research Assistant will support the CognoMND™ team by annotating speech recordings collected during verbal fluency tasks. You will use software such as Praat and Audacity to mark pauses, word boundaries, and other timing features in audio files. These annotations will contribute directly to the development and evaluation of the CognoMND™ cognitive screening tool.
Main Responsibilities:
- Listen to speech recordings and accurately label pauses and word onsets/offsets
- Use Praat and Audacity (training provided) to annotate audio files
- Follow established annotation guidelines to ensure consistency and quality
- Keep organised records of completed work
- Assist with inter-rater reliability checks
This is a structured, independent role involving careful attention to detail and contributes to research with real clinical and translational relevance. There may also be opportunities to support additional aspects of the speech-analysis workflow or to gain insight into the wider CognoMND™ project, depending on project needs and the student’s progress and interests.
Person Specification:
Essential
- Current University of Sheffield undergraduate student
- Strong attention to detail and ability to focus on precise, repetitive tasks
- Comfortable using software tools and learning new interfaces
- Reliable, organised, and able to work independently
- Good file-management skills, including organising folders, naming files consistently, and handling datasets carefully
Desirable
- Interest in phonetics, speech analysis, psychology, neuroscience, computer science, or digital health.
- Familiarity with audio-editing or analysis software (e.g., Praat, Audacity), though full training will be provided.
To Apply: Applicants should send a CV and a short supporting statement describing their interest in the role and any relevant experience to [email protected]. Please use the subject line 'Research Assistant (Audio Labelling) - CognoMND™'