To Altos We have an opportunity available for a Data Scientist to work in the field of cells, genomics and related areas. Responsibilities - Generate insights and models from multi-omics datasets (using public and internal data) to understand patterns, trends and relationships within data to inform decision-making and solve problems. Design, develops and programs methods, processes, and systems to … across the company. Preferred Qualifications - Strong and demonstrable experience working in an AWS compute environment is a major advantage. Experience integrating prior knowledge from public databases (e.g., KEGG) into omics data analysis pipelines. The salary range for Cambridge, UK : - Scientist I, Data Science : £64,600 - £87,400 Senior Scientist I, Data Science : £88,000 - £132,000 Exact compensation may vary More ❯
rolling out GUI-based bioinformatic tools facilitating experimental design and analyses. Proven ability to communicate complex bioinformatic concepts to stakeholders and multidisciplinary teams. General expertise in analyzing and interpreting omics and other biological data sets using statistical and visualization approaches. Good organizational skills, including time management, ability to set priorities and adhere to deadlines. Strong attention to detail and problem More ❯
and computational scientists across Altos. Influence best practices in areas such as Bayesian optimization, causal inference, building and assessing predictive models, analyzing biological networks, and analysis and visualization of -omics data. Maintain documentation and keep up-to-date as needed. Contribute to software releases (e.g. via GitHub, PyPI, Anaconda, Docker Hub). Who You Are The ideal candidate will be More ❯
techniques - including life science foundation models, generative design, uncertainty-aware decision making, and multi-modal data analysis. Responsibilities Perform data integration, mining, and analytics across chemical, biological, and multi-omics datasets to support target identification, hit discovery, and compound optimisation. Design and develop robust machine learning models. Collaborate with platform engineers to integrate ML models into production-grade pipelines, APIs More ❯
Cambridge, Cambridgeshire, United Kingdom Hybrid / WFH Options
ONE NUCLEUS
diseases pose a unique challenge due to limited patient data-especially at the single-cell level-making traditional modelling approaches difficult. This project tackles that challenge by integrating multi-omics and clinical data using hybrid models combining mechanistic, GenAI, and machine learning approaches. You'll contribute to building disease-specific Digital Twins using large-scale single-cell multi-omics datasets … Your work will help unlock new insights into disease mechanisms and inform potential treatments, diagnostics, and drug repurposing opportunities. Your role You will develop and apply methods to transform omics data into networks and executable models, collaborating closely with experts across the Petsalaki and Sheriff groups, Open Targets, EMBL-EBI, and the wider rare disease and biocuration community. You will … be primarily supervised by the Petsalaki group (Whole cell sigalling) and the Sheriff team (Biomodels). The Petsalaki group develops data driven network inference and modelling approaches from large omics datasets and the Sheriff team leads the development of innovative modelling approaches and maintenance of the Biomodels database. Key responsibilities include: - Generation of phenotype-specific networks from bulk-RNAseq and More ❯