
51 - 200 employees
🏥 Healthcare
💼 Consulting
📦 Logistics
Healthcare • Consulting • Logistics
Deciphex is a leading company revolutionizing the field of pathology by digitally networking pathologists globally and leveraging artificial intelligence to enhance the efficiency and quality of pathology reporting. Pathology is crucial to both healthcare delivery and drug development, and Deciphex addresses the growing demand-supply gap in this field by using digital pathology for workload balancing and AI for accelerating processes. The company specializes in providing digital pathology platforms, like Diagnexia and Patholytix, that support both clinical and research pathology. Deciphex enables on-demand remote consultations with subspecialty pathologists, accelerating diagnostic turnaround times and enhancing patient care. Their platforms are trusted by leading CROs and pharmaceutical companies, making Deciphex a pivotal entity in digital pathology and AI-driven solutions.
🕒 September 14
Where this job comes from
Posted on Deciphex's careers page, not through a job board
First seen by Remote Rocketship September 14
Still open on Deciphex's site. Checked 5 hours ago.

51 - 200 employees
🏥 Healthcare
💼 Consulting
📦 Logistics
Healthcare • Consulting • Logistics
Deciphex is a leading company revolutionizing the field of pathology by digitally networking pathologists globally and leveraging artificial intelligence to enhance the efficiency and quality of pathology reporting. Pathology is crucial to both healthcare delivery and drug development, and Deciphex addresses the growing demand-supply gap in this field by using digital pathology for workload balancing and AI for accelerating processes. The company specializes in providing digital pathology platforms, like Diagnexia and Patholytix, that support both clinical and research pathology. Deciphex enables on-demand remote consultations with subspecialty pathologists, accelerating diagnostic turnaround times and enhancing patient care. Their platforms are trusted by leading CROs and pharmaceutical companies, making Deciphex a pivotal entity in digital pathology and AI-driven solutions.
• Lead advanced data-science research supporting the development and validation of AI for toxicologic pathology and translational research • Translate complex scientific questions into rigorous datasets, experiments, benchmarking frameworks, and qualified analytical evidence • Curate, characterise, and analyse large preclinical and translational pathology datasets, including whole-slide images, structured study data, annotations, and associated metadata • Lead 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 • 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 • Develop and standardise data-processing pipelines and validation routines supporting 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 morphological findings, lesion terminology, and diagnostic reasoning • Collaborate with AI, software, and product teams to align research outputs with Deciphex’s scientific and product roadmap • Convert exploratory research into reproducible methods, scientific publications, evidence packages, and future product capabilities
• 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 • 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 • Must be eligible to work in Ireland; the employer cannot offer Irish work permits or visa sponsorship
• Healthcare benefits • Competitive annual leave • Meaningful work contributing to better patient outcomes • Opportunity to work alongside a world-class high performing team in a hyper-growth startup environment • Opportunity to work on exciting, challenging and unique projects • Regular performance feedback • Significant career growth opportunities • Highly collaborative and supportive multicultural team
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