Sort by
Refine Your Search
-
Listed
-
Employer
- ; Newcastle University
- ;
- ; The University of Manchester
- Newcastle University
- ; University of Leeds
- ; University of Oxford
- ; University of Reading
- ; University of Sheffield
- Cranfield University
- ; University of Exeter
- ; University of Nottingham
- University of Nottingham
- ; Aston University
- ; City St George’s, University of London
- ; Cranfield University
- ; Queen's University Belfast
- ; Swansea University
- ; University of Birmingham
- ; University of East Anglia
- ; University of East London
- ; University of Portsmouth
- ; University of Southampton
- ; University of Warwick
- Abertay University
- UNIVERSITY OF EAST LONDON
- University of Cambridge
- University of East London
- University of Sheffield
- 18 more »
- « less
-
Field
-
'Type of Study', ‘Full Time’ in ‘Mode of Study’, ‘2025’ in ‘Year of Entry’, code ‘8370F’ in ‘Course Title’, blank in ‘Research Area’. Press ‘Search’, select ‘PhD Population Health Sciences (FT)’, and
-
’ to identify your programme of study: Search for the ‘Course Title’ using the programme code: 8856F. Leave the ‘Research Area’ field blank Select ‘PhD in Process Industries; Net Zero (PINZ’) as the
-
score of 7.0 overall with a minimum of 6.5 in all sub-skills. How to apply For information about how to apply for this studentship, see www.ncl.ac.uk/postgraduate/fees-funding/search-funding/?code
-
Sciences, Environmental Sciences, Earth Sciences, Material Sciences, Biochemistry. Must have analytical chemistry skills and good numeracy; experience of mathematical coding would be desirable. Start date 1
-
of the supervisory team will share code and provide support where needed. Feasibility: Objectives for this project are well defined and the student will have the flexibility to tackle the objectives that align most
-
may decide to implement a same format slightly differently, leading to irreproducible results, non-portable code, hard-to-find bugs, and other unexpected behaviours. On the backdrop of this complex
-
Step 1: Submit your application to the QBS PhD programme via the QUB portal and enter the code QBSPGR2025/26 in the funding section: 🔗 myportal.qub.ac.uk Step 2: Email the following documents to Louise
-
, gathering and coding morphological and geospatial data. You will be encouraged to collaborate in writing the publication arising from this work. Student profile: The applicant must be meticulous, enthusiastic
-
the collaborative interaction of the student and the supervisors who will actively participate in all stages of the project. Input data and training for the use of the code and global sensitivity analysis techniques
-
upper second-class honours degree (or equivalent) in Engineering, Physics, or Applied Mathematics. Experience in coding and CFD is advantageous but not mandatory—an eagerness to learn and innovate is key