Applied Cognitive Researcher
Location: HCMC - VN
Reports to: CTO / CSO
Collaborates with: AI, Signal Processing, Mobile, Product, Business Teams
About Brain-Life
Brain-Life is developing an AI-powered neurofeedback wearable, using multimodal phyisological neural signals, designed to help individuals monitor and improve people's life quality (such as cognitive performance, mental workload regulation, and stress recovery) in real time.
Our mission is to transform multimodal brain and physiological signals into actionable, evidence-based interventions that measurably improve focus and relaxation within minutes.
We are seeking an Applied Cognitive Researcher who can bridge scientific research and product development.
Role Overview
We are looking for a translational researcher who understands cognitive science and human performance, who is knowledgable and can convert research insights into product features, technical requirements, and measurable user benefits.
This is not a purely academic role. You will work at the intersection of Psychology, Neuroscience, and Computer Science, specifically
- Cognitive neuroscience
- Bio-signal interpretation
- AI-driven state modelling
- User-centred product design
Your work will directly shape Brain-Life's core differentiation: fast, measurable improvement in cognitive performance and stress regulation.
Key Responsibilities
1. Cognitive State Modelling
- Define practical models for mental states such as: Cognitive workload, Sustained attention, Mental fatigue, Stress–recovery balance
- Work closely with AI engineers to refine classification logic and validation frameworks.
- Establish real-world validation approaches and ground-truth strategies, based on scientific & validated solutions.
2. Neurofeedback & Intervention Design
- Identify and evaluate evidence-based micro-interventions (e.g., HRV breathing, alpha neurofeedback, short cognitive resets).
- Define: computer-based intervention method (such as intervention triggers, duration and expected physiological response, measurable success criteria)
- Design and conduct human experiments to assess the intervention's effectiveness (such as Time-to-effect, Effect size, User adherence, Short-term and longitudinal improvement)
3. Applied Human Research
- Design and run user studies involving: Cognitive workload paradigms (e.g., working memory tasks), Behavioural performance measures, Self-report scales, Physiological validation
- Conduct UX testing of intervention strategies.
- Interpret multimodal bio-signal data in real-world environments.
- Deliver actionable insights for product iteration.
4. Research-to-Product Translation
- Convert scientific findings into: Product features, AI feature requirements, UX recommendations, Clear user-facing metrics (e.g., focus score, relaxation index)
- Collaborate closely with product and engineering teams to ensure research is embedded into deliverable solutions.
- Support evidence-based product claims and validation materials.
5. Business & Customer Insight Integration
- Work with business and product teams to translate user pain points into research questions.
- Ensure interventions produce perceivable improvements within short sessions.
Required Skills & Experience
- Practical experience in applied research related to cognitive states, attention, behaviour, or human performance.
- Experience working with business team, product team, with the ability to understand business needs.
- Familiarity with research methodologies such as experiments, behavioural assessment, or user studies.
- Ability to read and understand scientific literature and extract relevant insights.
- A proactive mindset with interest in applying science to real-world products and business problems.
- Strong communication skills to translate scientific findings into actionable outcomes.
Nice-to-Have Qualifications
- BSc (or higher) in Neuroscience, Cognitive Science, Biomedical Engineering, or related fields.
- Experience with EEG, fNIRS, HRV, or wearable bio-signal systems.
- Proficiency in Python, MATLAB, or R.
- Understanding of bio-signal processing and feature extraction.
- Experience in digital health, neurotechnology, or wearable device development.
What Success Looks Like
Within 6–12 months, you will have:
- Defined Brain-Life's operational cognitive state framework.
- Validated rapid micro-interventions with measurable physiological impact.
- Improved classification and intervention logic in collaboration with AI engineers.
- Contributed to measurable improvements in user focus and relaxation.
- Enabled evidence-backed differentiation for product and subscription strategy.
Why Join Brain-Life
This role is central to transforming Brain-Life from a signal-measurement wearable into a cognitive performance optimization platform.
You will help build a system that not only detects mental states - but actively improves people's quality of life, in real time.
