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Qualitative Team Lead

Nottingham (Hybrid, 3 days per week)

£80,000 to £100,000

This is a rare opportunity to lead and shape a qualitative insight function within a business that seamlessly blends creative, strategy, and research. You will have the autonomy to define the qualitative offering while working on high-profile, global brands, with clear visibility at senior leadership level.

The Company

They are a well-established, large-scale creative and brand communications business with a significant in-house insight and strategy capability. Operating a collaborative, integrated model, they bring together creative, data, and research specialists to deliver impactful work for major international clients. The organisation is investing in growing its insight function, with qualitative research playing a central role in that evolution. You will join an environment that values curiosity, innovation, and commercial impact.

The Role

You will take ownership of the qualitative research function, leading both delivery and strategic direction. Responsibilities include:

• Leading and developing a team of qualitative researchers, with responsibility for hiring, coaching, and performance
• Designing and delivering high-quality qualitative research projects across a range of methodologies
• Partnering with account and strategy teams to support key client relationships and drive growth
• Playing a central role on major client accounts, contributing to insight-led decision making
• Introducing and scaling new methodologies, including ethnography, semiotics, and digital or UX research
• Contributing to proposals, pitches, and broader business development activity
• Ensuring high standards of storytelling, presenting insight that drives action
• Collaborating across creative, strategy, and data teams within a matrix structure

Your Skills and Experience

To succeed in this role, you will bring:

• Strong commercial experience in qualitative research within an agency environment
• Proven ability to lead, mentor, and grow a team or practice area
• Deep expertise across qualitative methodologies, with a creative and flexible approach
• Experience working with large, complex or global brands
• Confidence in senior client engagement and stakeholder management
• Commercial awareness, including involvement in proposals, pitching, or account growth
• Interest in innovation, with exposure to areas such as behavioural science, cultural insight, or emerging qual techniques

What They Offer

• Opportunity to shape and grow a qualitative function with genuine autonomy
• Exposure to senior leadership and involvement in strategic decision making
• Strong existing client base with high-profile global work
• Clear progression and the chance to expand influence across insight, strategy, and creative

How to Apply

If you are interested in leading a high-impact qualitative function in a collaborative and creative environment, please apply with your CV.

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ML Scientist / Researcher

Oncology AI · Foundation Models · Life Sciences

Remote

About the Role

We are building foundation models trained on human tumor biology – one of the most consequential and technically demanding challenges at the intersection of AI and medicine. As an ML Scientist, you will be a core research contributor designing and training these models across multimodal omics datasets, partnering closely with biologists and fellow research scientists to advance the state of the art in oncology AI.

This is a research-forward role for scientists who want their work to matter. We are looking for people with a track record of research excellence – those who have gone deep on model architecture, training dynamics, and rigorous experimental design. If you have built models from the ground up and published findings, we want to talk.

What You’ll Do

• Design and train large-scale foundation models on multimodal biological datasets, including genomics, transcriptomics, and other omics modalities
• Collaborate deeply with computational biologists, research scientists, and domain experts to translate biological questions into tractable modeling problems
• Drive the full research lifecycle: hypothesis formation, experimental design, model development, and rigorous analysis of results
• Contribute to agentic AI systems that reason over complex biological data
• Communicate findings internally and, where appropriate, through peer-reviewed publication

What We’re Looking For

Must-Haves

• Strong research background, typically evidenced by a PhD in machine learning, computational biology, statistics, physics, or a related quantitative field – or equivalent industry research experience
• Demonstrated ability to build and train models end-to-end, including experimental analysis and iteration
• Research excellence: first-author publications at top ML, AI, or computational biology venues are a strong positive signal
• Deep familiarity with foundation model concepts: pretraining, self-supervised learning, attention mechanisms, and large-scale training
• Comfort working at the intersection of biology and machine learning – even without a formal biology degree

Nice-to-Haves

• Experience with biological or omics data (genomics, proteomics, pathology imaging, etc.)
• Prior work in multimodal learning or multi-omics integration
• Familiarity with agentic AI systems or tool-use frameworks
• Background in oncology or disease biology

What This Role Is Not

This is not a production ML engineering or MLOps role. We are not looking for candidates whose primary experience is model deployment, serving infrastructure, or engineering-heavy systems work. The emphasis here is firmly on research depth and model development.

Compensation & Location

Base Salary: $250,000 – $288,000 (depending on experience) + equity

Location: Remote-friendly; office in South San Francisco, CA

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Machine Learning Scientist

Remote (USA only)

About the Role

A frontier AI-driven bio-tech company is hiring a Machine Learning Scientist to help develop next-generation foundation models at the intersection of AI and biology.

This is an individual contributor role for a researcher who enjoys taking ideas from concept to experimentation, working on challenging problems, and collaborating with a highly technical team.

Responsibilities

• Design, train, and evaluate state-of-the-art machine learning and foundation models.
• Rapidly prototype and test new research ideas.
• Develop benchmark tasks and evaluation frameworks.
• Collaborate closely with researchers, scientists, and engineers.
• Contribute to publications and technical presentations.

Ideal Background

• PhD in Computer Science, Machine Learning, AI, Physics, Mathematics, Computational Neuroscience, or a related quantitative field.
• Strong publication record at leading conferences such as NeurIPS, ICML, ICLR, CVPR, or equivalent venues.
• Experience building models in PyTorch and conducting original machine learning research.
• Background in foundation models, LLMs, computer vision, multimodal learning, generative AI, robotics, or scientific machine learning.

Biology experience is a plus but not required. Exceptional researchers from computer vision, language modeling, robotics, autonomous driving, and other highly quantitative fields are encouraged to apply.

Why Join?

• Work on cutting-edge machine learning research with real-world impact.
• Collaborate with world-class researchers and scientists.
• Help shape the future of AI-driven scientific discovery.

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AI Engineer
San Francisco, California

Remote

$200,000 – $220,000 + Equity

About the Company

This innovative health tech startup is working to improve the oncology drug development process by providing better patient data to drug developers as well as better access to clinical trials for patients. This series B startup is expending to meet demand.

About the Role

As an AI Engineer, you will design and deliver applied AI systems (LLMs/CV/multimodal) that automate clinical variable abstraction and clinical note generation-with repeatable validation, robust documentation, and HITL feedback loops. Heavy emphasis on data engineering and backend rigor to make models usable and efficient.

Role Responsibilities

• Build models and pipelines across EMR/EHR, imaging, clinical reports
• Translate ambiguous clinical requirements into measurable ML objectives
• Define metrics, design experiments, estimate error; review peer work
• Deliver validated AI components for abstraction/note generation; meaningfully reduce manual QA workload via HITL; standardize documentation/testing; establish performant data manipulation patterns (e.g., PySpark, SQL/Postgres) that speed iteration.

Key Requirements

• Python
• Pytorch or Tensorflow
• Data engineering: PySpark, SQL, Postgres, query tuning, data modeling
• Cloud data platforms (e.g., Databricks, S3/Snowflake/Azure/GCP)
• Nice to have experience in oncology/biotech/health tech

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