Neuroscience QA Lead - AI Training

There is no immediate project assignment. Qualified candidates will join the expert network and receive priority consideration when relevant neuroscience or cognitive science AI training opportunities become available.

Job Details

Country: United Arab Emirates
City: Dubai
Industry: Research
Function: Quality Assurance
Salary: 13000-21000
Estimated salary range based on similar jobs in the job city; please confirm the final offer with the employer.
Gender: Any
Candidate Nationality: Any
Job Type: Contract - Remote - work from home

Role Context

The Neuroscience Quality Assurance Lead will oversee the reliability of scientific content used to train and evaluate advanced artificial intelligence systems. Assignments may involve reviewing explanations of brain function, cognitive theories, experimental findings, neuroimaging results, behavioral studies, neural mechanisms, and research-based claims about cognition or mental processes.

The successful candidate will identify neuromyths, unsupported causal conclusions, pseudoscientific claims, incorrect terminology, flawed study interpretation, weak statistical reasoning, and misleading clinical implications. The role also includes coaching contributors, maintaining project documentation, supporting onboarding, coordinating quality alignment, and improving scalable review systems.

Key Responsibilities

* Review neuroscience and cognitive science AI training items against detailed project rubrics and scientific quality standards.
* Evaluate scientific accuracy, conceptual precision, evidence use, clarity, formatting, and instruction compliance.
* Assess explanations involving neuroanatomy, neural signaling, cognition, perception, attention, memory, language, learning, and decision-making.
* Review research summaries, experimental interpretations, cognitive theory applications, and brain-behavior claims.
* Identify neuromyths, pseudoscientific statements, unsupported conclusions, and inaccurate representations of scientific evidence.
* Check whether causal claims are justified by the underlying study design and available data.
* Evaluate descriptions of behavioral experiments, neuroimaging studies, computational models, and neuropsychological assessments.
* Review statistical interpretations for overclaiming, omitted limitations, weak inference, and misuse of correlation.
* Flag clinically misleading conclusions involving neurological conditions, mental health, diagnosis, treatment, or cognitive performance.
* Assess whether AI-generated responses distinguish established findings from hypotheses, emerging evidence, or speculation.
* Verify scientific terminology, methodological descriptions, and explanations of neural mechanisms.
* Spot-check work completed by researchers, trainers, annotators, science writers, reviewers, and QA contributors.
* Provide precise written feedback explaining each scientific issue and the corrective action required.
* Escalate recurring, critical, ethically sensitive, or high-risk quality concerns to project stakeholders.
* Communicate new guidelines, workflow changes, and neuroscience-specific review expectations through Discord.
* Respond to contributor questions involving cognition, neural processes, study design, statistics, ethics, clinical caution, and rubric interpretation.
* Contact inactive trainers and QAs, encourage participation, record follow-ups, and flag availability concerns.
* Create and maintain style guides, FAQs, trackers, quality notes, reference examples, honeypots, calibration tasks, and onboarding materials.
* Conduct remote onboarding and training sessions for neuroscience trainers, reviewers, and QAs.
* Ensure contributors apply evolving neuroscience and cognitive science standards consistently.
* Analyze recurring quality gaps and recommend practical improvements to review workflows.
* Maintain accurate records of reviews, contributor feedback, performance patterns, and corrective actions.

Ideal Profile

* Bachelor\'s, Master\'s, PhD, MD-PhD, or equivalent professional background in Neuroscience, Cognitive Science, Psychology, Neurobiology, Cognitive Psychology, Computational Neuroscience, Biology, Biomedical Sciences, or a closely related field.
* Minimum 3 years of experience in neuroscience or cognitive science research, teaching, laboratory work, academic review, experimental design, data analysis, or science communication.
* Strong English communication skills for interpreting complex guidelines and delivering clear scientific feedback.
* Thorough understanding of neural systems, cognition, perception, attention, memory, learning, language, and decision-making.
* Sound knowledge of neuroanatomy, neural signaling, research methodology, and brain-behavior relationships.
* Ability to identify unsupported causal claims, incorrect terminology, pseudoscience, and misleading clinical implications.
* Familiarity with EEG, fMRI, behavioral experiments, computational modeling, neuropsychological assessment, or cognitive testing is preferred.
* Experience using Python, R, MATLAB, statistical tools, or scientific data workflows is beneficial.
* Strong understanding of experimental design, research limitations, statistical caution, and evidence interpretation.
* Ability to evaluate sensitive claims involving cognition, behavior, mental health, and neurological conditions responsibly.
* Experience leading or supporting researchers, reviewers, educators, annotators, science writers, or QA teams is strongly preferred.
* Strong attention to scientific detail, terminology, methodology, and ethical boundaries.
* Confidence using Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems.
* Experience developing style guides, calibration tasks, onboarding resources, FAQs, and quality documentation is beneficial.
* Familiarity with AI training, data annotation, large language model evaluation, scientific QA, or rubric-based review is advantageous.
* Availability to complete an AI interview, a domain-specific assessment, and a recruiter interview.
* Comfortable working independently in a fast-moving remote environment.

Skills Set

* Neuroscience quality assurance
* Cognitive science
* Neuroanatomy
* Neural signaling
* Brain-behavior relationships
* Cognitive psychology
* Perception and attention
* Memory and learning
* Language processing
* Decision-making
* Experimental design
* Research methodology
* Statistical interpretation
* Scientific literature review
* Behavioral experiments
* EEG
* fMRI
* Neuropsychological assessment
* Computational neuroscience
* Cognitive modeling
* Python
* R
* MATLAB
* Scientific terminology review
* Neuromyth detection
* Pseudoscience identification
* Clinical caution review
* Research ethics
* Rubric-based assessment
* AI-generated scientific content evaluation
* Large language model evaluation
* Data annotation quality
* Trainer performance monitoring
* Written scientific feedback
* Style guide development
* Calibration task design
* Contributor onboarding
* Remote team coordination
* Discord
* Google Sheets
* Google Docs
* Quality trackers
* Process improvement

Why Join Us

This opportunity enables neuroscience and cognitive science professionals to apply research expertise within the rapidly developing artificial intelligence sector. The work directly influences how AI systems explain brain function, interpret scientific studies, assess cognitive claims, represent neurological evidence, and avoid pseudoscientific or clinically misleading conclusions.

Qualified experts will become part of a flexible remote network and receive early consideration for relevant future assignments. The role also provides exposure to emerging AI evaluation methods, international scientific teams, complex research datasets, and quality frameworks used to improve next-generation language models.

About the Company

YO IT Consulting connects scientists, researchers, and domain specialists with remote AI training and quality evaluation projects. Operating from Dubai, United Arab Emirates, the company recruits experts worldwide whose scientific judgment helps improve the accuracy, evidence awareness, ethical reliability, and reasoning capabilities of modern artificial intelligence systems.