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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in machine learning techniques and statistical principles to enhance mental health outcomes through data analysis and predictive modeling. Proven ability to lead research initiatives, mentor junior scientists, and publish findings in high-impact journals.
Highest-signal resume keywords
PhD In Computational Science Or AI-Related FieldExpertise In LLM-Related ResearchProficiency In Python And TypescriptExperience With Neural Deep Learning And Machine LearningStrong Publication Record In AI Research
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningPredictive ModelingData AnalysisFeature-Extraction MethodsReinforcement LearningModel Fine-TuningStatistical PrinciplesVersion Control SystemsNeural Deep LearningLLM Evaluation
Soft Skills
MentoringCommunicationCollaborationProblem-SolvingLeadership
Tools & Technologies
AWSGCPAzureDockerSQLNoSQLGit
Industry Keywords
Mental HealthCausal MechanismsScientific ExperimentsPeer-Reviewed JournalsIntellectual Property
Tech Stack
Tools & technologiesAWSAzureCloudDockerGoogle Cloud PlatformNoSQLPythonSQLTypeScript
About the role
Key responsibilities & impact- Use cutting-edge ML techniques to improve patient trajectories and outcomes
- Use existing data to identify meaningful mental health representation spaces
- Identify causal mechanisms driving recovery from mental health conversations
- Predict trajectories of mental health outcomes and build recommender systems for interventions
- Design and run rigorous scientific experiments to validate methods and publish findings in high-impact peer-reviewed journals
- Lead patent submissions to protect intellectual property
- Work with clinical research and ML engineering teams to build product-ready, clinically evaluated tools
- Drive continuous improvement through experimentation, iterative development, testing and optimisation
- Translate complex scientific challenges into impactful solutions
- Mentor and guide junior scientists and colleagues
- Present findings in internal and external scientific meetings and events
Requirements
What you’ll need- A PhD in computational science or an AI-related field, plus 2+ years of experience in a postdoctoral AI researcher role
- Strong publication record in AI research in cutting-edge conference proceedings or peer-reviewed journals
- Expertise in LLM-related research and methods development
- Experience with neural deep learning and machine learning
- Expert-level proficiency in Python, Typescript or related languages
- Experience in data analysis of large language-based datasets, feature-extractions methods, and prediction modelling
- Experience with reinforcement learning and model fine-tuning (e.g. RLHF/RLAI)
- Expertise in statistical principles specifically in the context of LLM evaluation and user activity analytics
- Proficiency with version control systems (preferably Git) and databases (SQL or NoSQL)
- Hands-on experience with major cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker) desirable
- Ability to work from the London (Spitalfields) office on Tuesdays and Thursdays
- Visa sponsorship for skilled workers possible
Benefits
Comp & perks- 29 days of holidays (25 regular days and 4 Quarterly Life Days) + UK bank holidays
- Access to mental health support
- Company-wide meetups
- Generous parental leave package
- 100% reimbursement for work-related books and materials
- Flexibility with remote working
- Free gym sessions
- Socials
- Guest speaker events