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computational chemistry PhD Projects, Programs & Scholarships

We have 174 computational chemistry PhD Projects, Programs & Scholarships

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Showing 1 to 10 of 174
  EPSRC Centre for Doctoral Training in Theory and Modelling in Chemical Sciences
University of Bristol School of Chemistry
Fully funded 4-year doctoral studentships. Opportunities are available to join the UK's only Centre for Doctoral Training dedicated to computational and theoretical chemistry.
Details
Type/Funding
  EPSRC Centre for Doctoral Training in Theory and Modelling in Chemical Sciences
University of Oxford
Fully funded 4-year doctoral studentships. Opportunities are available to join the UK's only Centre for Doctoral Training dedicated to computational and theoretical chemistry.
Details
Type/Funding
  EPSRC Centre for Doctoral Training in Theory and Modelling in Chemical Sciences
University of Southampton
Fully funded 4-year doctoral studentships. Opportunities are available to join the UK's only Centre for Doctoral Training dedicated to computational and theoretical chemistry.
Details
Type/Funding
  Graduate Studentship in Theoretical/Computational Chemistry: calculations of the spin dynamics and magnetic sensitivity of cryptochromes and related compounds
University of Oxford Department of Chemistry
  Prof P Hore
Application Deadline: 25 January 2019
Ref. PJH/ERC/Theo/2019. Applications are invited for a DPhil studentship in Theoretical/Computational Chemistry available from 1st April 2019, to work with Professors Peter Hore and David Manolopoulos.
Details
Type/Funding
  Integrative Computational Biology and Machine Learning: Combining computational biology, computational chemistry, and machine learning techniques with biological big data to unravel the higher genomic code of life
University of Oxford Radcliffe Department of Medicine
  Dr A Sahakyan, Prof P McHugh
Application Deadline: 11 January 2019
In the Sahakyan Group, we strive to make computational biology maximally independent from empirical experimental data, by basing our models and predictions on genomic sequences and core biological mechanisms.
Details
Type/Funding
  Decision making through artificial chemical intelligence
University of York Department of Chemistry
  Dr J Slattery, Prof I J S Fairlamb, Dr J M Lynam
Application Deadline: 9 January 2019
Automation will transform the chemical landscape. Powerful robotic platforms can perform reactions or analyses much more rapidly than traditional approaches.1 Ever faster computers allow huge numbers of molecules to be studied in an automated way using computational chemistry.
Details
Type/Funding
  Mapping the low-lying excited states of aromatic and antiaromatic ions via experiment and theory
University of York Department of Chemistry
  Dr C E Dessent, Dr P B Karadakov
Application Deadline: 9 January 2019
Aromaticity is one of the most fundamental concepts in chemistry.
Details
Type/Funding
  Green Chemistry for Selective Functionalisation of C-H bonds to C-C and C-X bonds
University of Strathclyde Pure and Applied Chemistry
  Prof JA Murphy, Prof T Tuttle
Applications accepted all year round
This project is funded at the University of Strathclyde (supervisor for this studentship). Prof John Murphy. This project arises from recent discoveries of new chemistry in the Murphy group and involves conversion of C-H to C-X bonds.
Details
Type/Funding
  Computational Identification of New Inorganic Materials for Automotive Applications
University of Liverpool Department of Chemistry
  Prof M Rosseinsky, Dr M Dyer
Application Deadline: 14 May 2019
This position will remain open until a suitable candidate has been found. This 42 month PhD project will apply new computational techniques to discover materials for application as pigments in the automotive industry with reduced environmental and energy impact compared to existing materials.
Details
Type/Funding
  Machine learning in quantum chemistry - using machine learning to improve the results of quantum chemical calculations
University of Sheffield Department of Chemistry
  Dr JG Hill
Applications accepted all year round
Machine learning methods have seen a great deal of recent success in a number of technological fields, and these techniques from applied statistics and computer science are poised to change the fields of computational and theoretical quantum chemistry.
Details
Type/Funding
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