Lead AI Scientist for Mental Health ResearchPythonSQL

Only Coders
Oxford
1 year ago
Applications closed

Related Jobs

View all jobs

Data Scientist (Southampton)

Machine Learning Scientist III

Principal Data Scientist

Data Scientist

Senior Data Scientist

Senior Geospatial Data Scientist

Title:Lead AI Scientistfor Mental Health Research(Python/SQL)

Industry:Healthtech

Location:Oxford

WorkForm:HybridPermanent Fulltime

Salary:50k 60k perannum (depending on relevant workexperience)


Ourclient uses advanced AI and NLP to transform mental health anddementia research. Their advanced platform enhances patientcharacterization and supports precision neuroscience enablingtargeted interventions and improving patientoutcomes.

Theyare looking for a Lead AI Scientist who will lead a team indeveloping NLP models to structure psychiatric electronic healthrecords aiding research in mental health and dementia.

Therole involves close collaboration with research engineering andclient engagement teams to ensure the models are accurateclinically valid and effective for researchapplications.


Responsibilities:

  • Leadingand managing a team of AI scientists and healthcare data analystsproviding mentorship andguidance.
  • Developingand refining Natural Language Processing (NLP) models to structurepsychiatric electronic healthrecords.
  • Collaboratingwith research engineering and client engagement teams to integrateAI models into the data processing pipeline and ensure theiroutputs meet userrequirements.
  • Conductingexploratory research prototyping and literature reviews to developnovel AI applications for mental health anddementia.
  • Ensuringthe accuracy clinical validity transparency and scalability of AImodels.
  • CommunicatingAI development plans and progress to the widercompany.
  • Disseminatingresearch findings through peerreviewed publications clientpresentations and conferenceattendance.
  • Growingthe network of academic healthcare and industry collaborators inthe clinical AI space.
  • Preparinggrant applications to support AI developmentprojects.


Requirements


  • PhDlevelqualification (or equivalent industry experience) in a field with asubstantial component of applied AImethods.
  • Highlevel of knowledge in machine learning methods applications andvalidation methods.
  • Expertisein Natural Language Processing (NLP) techniques includingexperience with Large Language Models for textprocessing.
  • Proficiencyin Python (or another programming language with foundational Pythonskills).
  • Experiencein team leadership mentorship or supervision with a desire to helpgrow the team of AI scientists through line management andtechnical leadership.
  • Stronginterest in healthcare applications of AI and NLP particularly inmental health and dementia.
  • Excellentinterpersonal teamwork and collaborationskills.
  • Abilityto translate complex concepts and communicate effectively withnonexpert stakeholders in various formats (verbal written documentspresentations).
  • Experiencein line management.
  • Sectorexperience in mental health research data and/or careprovision.
  • Experienceworking in a collaborative version control workflow (e.g. GitBitbucket).
  • Knowledgeof SQL particularlyPostgreSQL.



Benefits

  • 25daysof annual leave plus bank holidays.
  • 3additional days of annual leave after 3 years of employment.
  • Healthinsurance planincluding24/7virtual GP mental health support money towards dental treatmentsight tests (plus additional plan for dependents) andhealth/wellbeing discounts (including gym membership).
  • 6%companycontributorypension.
  • Freshfruit and drinks in theoffice.

Emailyour CV direct to




PhD-level qualification (or equivalent industry experience) in afield with a substantial component of applied AI methods. Highlevel of knowledge in machine learning methods, applications, andvalidation methods. Expertise in Natural Language Processing (NLP)techniques, including experience with Large Language Models fortext processing. Proficiency in Python (or another programminglanguage with foundational Python skills). Experience in teamleadership, mentorship, or supervision, with a desire to help growthe team of AI scientists through line management and technicalleadership. Strong interest in healthcare applications of AI andNLP, particularly in mental health and dementia. Excellentinterpersonal, teamwork, and collaboration skills. Ability totranslate complex concepts and communicate effectively withnon-expert stakeholders in various formats (verbal, writtendocuments, presentations). Experience in line management. Sectorexperience in mental health research, data, and/or care provision.Experience working in a collaborative version control workflow(e.g., Git, Bitbucket). Knowledge of SQL, particularlyPostgreSQL.

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.