Organization profile

Organisation profile

SAMBa is the EPSRC Centre for Doctoral Training in Statistical Applied Mathematics at Bath. In a world of fast moving decision making, based on myriad sources of large and complex data, the need to robust collection, analysis and interpretation of that data is essential. Statistical Applied Mathematics brings together the research areas of applied maths, stochastic modelling, numerical analysis and statistics, in a multidisciplinary and industrially motivated environment. It provides researchers with tools to not only undertake novel and creative research, but also to communicate their results and build successful collaborations across traditional boundaries. SAMBa is funded by EPSRC and the University of Bath, based in the Mathematical Sciences department but with collaborators from across campus, the UK, internationally and outside of academia. Students undertake a four year programme, which consists mainly of taught courses in year one and research in years two to four. We also run biannual Integrative Think Tanks (ITTs) which bring together students, academics, and partners to formulate mathematical approaches to high level industrial and societal challenges. For more information see our website: http://www.bath.ac.uk/centres-for-doctoral-training/epsrc-centre-for-doctoral-training-in-statistical-applied-mathematics-samba/

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    Projects

    Research Cloud Computing Pilot Project (OpenFOAM)

    Kelly, N., Cookson, A. & Fraser, K.

    8/06/2014/07/20

    Project: Research-related funding

    Non-stationary food frequency analysis using peaks-over-threshold models

    Kjeldsen, T. & Prosdocimi, I.

    1/06/2031/12/21

    Project: Research-related funding

    Research Output

    2D-layered Ti3C2/TiO2 hybrids derived from Ti3C2 MXenes for enhanced electromagnetic wave absorption

    Fan, B., Shang, S., Dai, B., Zhao, B., Li, N., Li, M., Zhang, L., Zhang, R. & Marken, F., 7 Apr 2020, In : Ceramics International.

    Research output: Contribution to journalArticle

    3D CFD optimisation of T-piece junction in engine inlet air path

    Liu, Y., Hopf, A. & Burke, R., 11 Jun 2020, (Acceptance date) Memorial Book for Prof Roland Baar.

    Research output: Chapter in Book/Report/Conference proceedingChapter

    AB0735 SEVERITY OF NAIL PSORIASIS SCORE (SNAPS) DEMONSTRATES LONGITUDINAL CONSTRUCT VALIDITY AGAINST THE MODIFIED NAIL PSORIASIS SEVERITY INDEX (mNAPSI) IN AN OBSERVATIONAL COHORT OF PATIENTS WITH PSORIATIC ARTHRITIS

    Antony, A., Saeed, S., Hart, D., Nair, P., Cavill, C., Korendowych, E., Mchugh, N., Lovell, C. & Tillett, W., 1 May 2020, BMJ Publishing Group Ltd.

    Research output: Other contribution

    Datasets

    Dataset for "User-testing guidelines to improve the safety of intravenous medicines administration: a randomised in-situ simulation study"

    Jones, M. (Creator), McGrogan, A. (Creator), Raynor, D. K. (Creator), Watson, M. (Creator) & Franklin, B. D. (Creator), University of Bath, 3 Jun 2020

    Dataset

    Dataset for "The importance of thermal modelling and prototyping in transitional shelter design"

    Fosas, D. (Creator), Moran, F. (Creator), Natarajan, S. (Creator), Orr, J. (Creator) & Coley, D. (Creator), University of Bath, 22 Nov 2019

    Dataset

    Dataset for "3D Printed Contactor for Enhanced Oil Droplets Coalescence"

    Al-Shimmery, A. (Creator), Mazinani, S. (Creator), Flynn, J. (Creator), Chew, J. (Creator) & Mattia, D. (Creator), University of Bath, 19 Jul 2019

    Dataset

    Student theses

    3D Electrical impedance tomography using planar arrays

    Author: Wu, Q. B., 16 Aug 2018

    Supervisor: Soleimani, M. (Supervisor)

    Student thesis: Doctoral ThesisMPhil

    File

    3D Face Recognition Using Multicomponent Feature Extraction from the Nasal Region and its Environs

    Author: Gao, J., 23 Nov 2016

    Supervisor: Evans, A. (Supervisor) & Li, R. (Supervisor)

    Student thesis: Doctoral ThesisPhD

    File

    A Bayesian Approach to Phylogenetic Networks

    Author: Radice, R., 1 Jan 2011

    Supervisor: Feil, E. (Supervisor)

    Student thesis: Doctoral ThesisPhD

    File