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Deciphex

AI Data Scientist

Location unstated

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hirly's read of this role

Role family
Data & ML
Seniority
Mid level
Work mode
On-site / unstated
First seen by hirly
14 Sept 2026

Derived automatically from the posting.

the posting

Location

Work from home in Ireland.

Eligibility to work

Unfortunately we cannot offer Irish work permits or Visa sponsorship.

About this Role

As a Senior AI Data Scientist in Research Pathology at Deciphex, you will lead advanced data-science research supporting the development and validation of AI for toxicologic pathology and translational research. Working at the interface of histopathology, computational pathology, and machine learning, you will translate complex scientific questions into rigorous datasets, experiments, benchmarking frameworks, and qualified analytical evidence.

Working closely with pathologists, AI researchers, software engineers, and product teams, you will ensure that model development is grounded in real tissue morphology, diagnostic reasoning, and unmet research needs. You will also support translational research activities, including biomarker discovery, IHC quantification, and tissue-based endpoint characterisation, and help convert exploratory research into reproducible methods, scientific publications, evidence packages, and future product capabilities.

You will play a leading role in pathology foundation-model research, designing training experiments, developing practice-relevant benchmarks, and translating exploratory research into reproducible methods and downstream pathology applications.

Key Responsibilities

Curate, characterise, and analyse large preclinical and translational pathology datasets, including whole-slide images, structured study data, annotations, and associated metadata

Lead the design and execution of advanced data-science and machine-learning research across toxicologic pathology and translational research applications

Design and conduct pathology foundation-model training experiments, including data-curation studies, training-recipe ablations, fine-tuning, and evaluation of learned representations for downstream pathology applications

Validate downstream pathology AI models through performance characterisation, confounder analysis, and evidence packages suitable for regulatory scrutiny

Build benchmarking datasets and practice-relevant evaluation tasks for foundation and downstream models, including non-clinical benchmarks grounded in whole-slide pathology use where no public standard exists

Develop and standardise data-processing pipelines and validation routines that support model development, benchmarking, and deployment

Support translational research applications, including biomarker discovery, IHC quantification, and tissue-based endpoint characterisation

Work directly with pathologists to ground datasets and model outputs in real morphological findings, lesion terminology, and diagnostic reasoning

Collaborate with the AI, software, and product teams to align research outputs with Deciphex's scientific and product roadmap

Required Skills and Experience

PhD in data science, bioinformatics, computational biology, biomedical science, statistics, computer science, or a related quantitative field (equivalent research experience may also be considered)

Strong proficiency in Python and relevant machine-learning and scientific-computing frameworks, such as PyTorch and scikit-learn.

Experience curating, integrating, and quality-controlling large imaging datasets and associated structured metadata

Demonstrable experience applying data science and machine learning to digital pathology, biomedical imaging, or complex biomedical datasets

Strong grounding in applied statistics and model validation, including experimental design and selection of clinically or operationally meaningful performance measures

Experience designing and conducting deep-learning experiments, including model training, evaluation, ablation studies, and systematic comparison of modelling approaches

Ability to translate scientific questions into well-defined datasets, analytical plans, validation strategies, and clear evidence-based conclusions

Experience developing reproducible analytical workflows using appropriate practices for version control, testing, environment and configuration management, provenance, and technical documentation

Ability to read and critically interpret scientific publications, technical standards, and relevant regulatory guidance

Excellent written and verbal communication in English, including the ability to produce clear technical and scientific documentation for specialist and non-specialist audiences

Demonstrated ability to work effectively across multidisciplinary and multi-organisation teams, managing competing scientific and delivery priorities

Desirable Skills and Experience

Working knowledge of histopathology, including tissue morphology, pathological findings and terminology, and the ability to discuss datasets and model outputs fluently with pathologists

Understanding of preclinical toxicology study design, treatment and control groups, endpoints, and histopathology workflows

Experience with whole-slide imaging, digital pathology platforms, image formats, annotation workflows, and large-scale image-data management

Experience with pathology foundation models, self-supervised learning, Vision Transformers, representation learning, model fine-tuning, or knowledge distillation

Experience training and evaluating deep-learning models using GPU, HPC, cloud, or distributed-computing infrastructure

Experience with translational pathology applications, such as biomarker discovery, IHC or multiplex-image analysis, tissue segmentation, and tissue-based endpoint characterisation

Experience collaborating with software engineers to translate research models and analytical workflows into maintainable, tested, and product-ready implementations

A record of peer-reviewed publication, conference presentation, or substantive delivery of applied AI research

About the Company

Through the work that we do, the team at Deciphex helps pharma to accelerate the process of essential drug development and helps patients to get timely and accurate diagnosis.

Founded in Dublin in 2017, Deciphex has scaled rapidly to a team of over 230 people and counting who are providing software solutions to address the pathology gap in research pathology and clinical areas. We have offices in Dublin, Exeter, Oxford, Toronto and Chicago and are expanding our team throughout the world.

We are software developers, clinical specialists, AI engineers, operations professionals and so much more, all working as one team to support our customers and patients. Our team culture is built on trust. We give our team the space they need to deliver results and the environment to ensure they can enjoy doing it.

We are looking for highly motivated individuals who are excited to take on challenges and value making a difference in their day-to-day work. This is a unique opportunity to make a difference in the emerging Digital Pathology field.

Read more about Deciphex here and more about our incredible team on our Careers Page here

What are the benefits of working with Deciphex?

Healthcare benefits

Competitive annual leave

A true sense of meaning in your work by contributing to better patient outcomes.

The opportunity to work alongside a world-class high performing team in a hyper-growth startup environment.

A chance to work on exciting,challenging and unique projects.

Regular performance feedback and significant career growth opportunities.

A highly collaborative and supportive multi cultural team.

Deciphex is an equal opportunities employer and we are committed to the principle of equality. All qualified applicants will be considered for employment without regard to age, race, religious beliefs, political views, gender identity, affectional or sexual orientation, national origin, family or marital status (including pregnancy), disability, membership of the travelling community or any other classification protected by applicable law.

A copy of our

Original posting on Deciphex's site ↗

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