GROUND TRUTH LABS

Engineering

MachineLearningScientist

£85–130k ~AI est. United Kingdom FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid+ candidates.

The Brief

“Machine Learning Scientist at GROUND TRUTH LABS. Skills: Machine learning, Deep learning, Image analysis, Biomarker development. Develop algorithms. Analyse cell morphology”

What You'll Achieve.

Improve patient outcomes; Drive clinical adoption; Make impact across organisation

Industry & Context.

Engineering
Problems you'll solve

Solve hard problems; Think critically; Develop effective strategies

Eligibility Requirements

Regular travel to London, Regular travel to Oxford

What They're Looking For.

Must Have

PhD or equivalent practical experience, Experience in deep learning, Experience in statistical analyses, Expertise in processing image datasets, Expertise in analysing image datasets, Ability to work independently, Ability to work in multidisciplinary team, Programming skills in Python, Experience with PyTorch

Nice to Have

Track record in computational pathology, Track record in single-cell transcriptomics analysis, Track record in sequencing, Clinical background, Knowledge of cancer biology, Expertise in multimodality integration, Post doctoral roles, Proven track record of publications, Contributions to machine learning codebases

What You'll Do.

Analyse cell morphology

Analyse tissue morphology

Design deep-learning models

Extract insights from histology data

Collaborate with cross-functional teams

Identify opportunities for solutions

Develop interpretable algorithms

Address clinical questions

Develop data pipelines

Maintain data pipelines

Support data science projects

Manage product inputs

Manage software inputs

Manage clinical inputs

Manage regulatory inputs

Translate research algorithms

Create clinical-grade tools

Communicate results to stakeholders

Communicate insights to decision-makers

Present conference abstracts

Stay up-to-date with developments

How You'll Work.

Team & Collaboration

Cross-functional teams; Interdisciplinary teams; Asynchronous teams; Multidisciplinary team

Communication Scope

Written communication; Concise communication; Engaged communication; Clear communication

Full Job Description

GROUND TRUTH LABS GTL is a well-funded, early-stage startup developing state-of-the-art digital technologies to better understand, diagnose and treat blood cancer patients. We have built an exceptional, small-by-design, interdisciplinary team to translate leading academic research into real impact on global health. Since 2023 we have made considerable progress in developing our technology, deploying our first generation of algorithms commercially with global biopharma companies, and working with world-leading academic medical centres to continue developing and validating new biomarker tools that improve patient outcomes. As a member of our small team, you will have the opportunity to help shape our journey and build on our principles of collaboration, focus, and invention. YOUR IMPACT We are looking for a Machine Learning Scientist to play a critical role in the development of new spatial biology biomarkers for haemato-oncology. You will develop algorithms that make use of the latest machine learning and computer vision techniques to analyse the cell and tissue morphology at different scales. We expect that you have an enthusiasm for AI products and a track record of interesting projects in image analysis to match. This is a highly creative, fast-paced environment. Our teams are interdisciplinary, you will work alongside engineering and clinical science to build robust algorithms and to develop methodologies that drive clinical adoption. We are an early stage company, you will have the opportunity to drive the research direction, lead on new projects and make an impact across the organisation. The successful candidate will be able to identify, build, and champion algorithm products in key strategic areas for GTL. WHAT YOU’LL DO - Design, develop and implement advanced deep-learning models to extract valuable insights from histology imaging data - Collaborate with cross-functional teams, including engineers, clinical experts, and product managers, to identify opportu

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