2 of 2 Permanent Predictive Modelling Jobs in the East of England

that best align with your skills, interests and university experience to strengthen your application. Roles Available in Location: Stevenage Education required: To apply for a placement in Data, Automation, & Predictive Sciences (DAPS), you must be studying for an Undergraduate Degree in a subject related to the role. Includes Life sciences, Biomedical Sciences, Engineering, Mathematics, Bioinformatics, Computer Science, Business Analysis … management, problem-solving, networking, data analysis and management, and role-specific technical skills. The Roles (6 available) This advert contains multiple roles. All roles are within the Data, Automation & Predictive Sciences Department. Please read each description carefully before applying. Role 1 - Research Data Science Degree requirements: Life sciences, Bioinformatics, Computational sciences, Statistics, Mathematics Placement Overview: Designing, building, and deploying … data analyses and predictive models for scientific discovery in GSK's research areas. Implementing and benchmarking computational methods leveraging cloud and AI/ML technologies to inform early target and medicine discovery decisions. Key Placement Learnings: Perform analyses and build predictive models using R and Python, following coding best practices and using cloud platforms. Process, analyze and integrate More ❯

complex biological systems by integrating data about biochemical components and help design interventions that direct cellular states along desired trajectories. This includes working with quantitative "big data" and building predictive models to develop novel theories. Our ultimate goal is to contribute to improving human lives through better-informed treatments. Responsibilities: - Contribute to modeling, simulation, and analysis of mechanistic or … establishing design principles of rejuvenated cells. Collaborating with both experimental 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 More ❯