Senior AI-Integrated Digital Twins Scientist

Earlham Institute; Norwich; Híbrido; GBP 39.000 - 53.000; Jornada completa

Descripción de la vacante

The Earlham Institute invites applications for a (Senior) Postdoctoral Research Scientist to advance AI integrated Digital Twins. The role focuses on predictive systems biology, combining mechanistic modelling with AI/ML and multimodal data to simulate biological states and perturbations.

We seek candidates with a PhD in a relevant quantitative field, strong programming skills (Python) and a track record in reproducible computational research.

Formación

• PhD awarded, or expected within six months, in computational/systems biology, bioinformatics, AI/ML, applied mathematics, physics, engineering, computer science or a related quantitative discipline.
• Strong programming skills and experience developing reproducible computational research workflows.
• Experience analysing high-dimensional omics data; ability to work across disciplinary boundaries.

Responsabilidades

• Develop new predictive systems-biology and Digital Twin methodologies; investigate personalization, uncertainty and counterfactual simulation.
• Parameterise, train and validate predictive models using heterogeneous biological data across multiple systems.
• Develop hybrid mechanistic-AI modelling approaches and ensure reproducible modelling workflows.
• Publish high-quality research and contribute to open models and benchmarks.
• Mentor researchers, participate in grant applications and group leadership activities.

Conocimientos

Mechanistic modelling

AI/ML for biology

Computational biology

Python programming

Scientific workflow/reproducibility

Model validation/uncertainty

Educación

PhD in computational/systems biology or related quantitative discipline

Herramientas

PyTorch

TensorFlow

JAX

Descripción del empleo

The Earlham Institute invites applications for a (Senior) Postdoctoral Research Scientist to advance AI integrated Digital Twins. The role focuses on predictive systems biology, combining mechanistic modelling with AI/ML and multimodal data to simulate biological states and perturbations.

We seek candidates with a PhD in a relevant quantitative field, strong programming skills (Python) and a track record in reproducible computational research.