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machine PhD Projects, Programs & Scholarships

We have 422 machine PhD Projects, Programs & Scholarships

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  Machine Learning and Integrative Approaches in Immunology: Developing machine-learning and mathematical models to understand heterogeneity of response to personalised cancer immunotherapy
  Dr H Koohy, Prof V Cerundolo, Prof T Dong, Prof A Simmons
Application Deadline: 11 January 2019
Cancer immunology is an area of cancer research that is gaining tremendous momentum. However, responses to immunotherapy are heterogeneous and patient care could be substantially improved by better understanding of how and why responses to immunotherapeutic approaches vary in different patients.
  Machine learning in quantum chemistry - using machine learning to improve the results of quantum chemical calculations
  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.
  A critical assessment of fault growth models using Machine Learning tools
  Dr T Alves
Application Deadline: 7 January 2019
Project Background. Lithological heterogeneities in subsurface units are capable of distributing stresses in distinct ways, leading to the nucleation of faults and fractures in specific stratigraphic intervals.
  Machine learning techniques for the optimisation and simulation of Metal Additive Layer Manufacturing process chains
  Dr S Bigot, Dr P Kerfriden, Dr Z Ji, Dr M Packianather
Applications accepted all year round
The aim of this PhD is to develop new data analytic tools (e.g. machine learning, data mining) to support the understanding, the optimisation and the Multi-scale and multi-physics simulation of metal Additive Layer Machining (ALM) process chains.
  MRC Precision Medicine DTP: Image analysis and machine learning for OCT image sequences
  Dr S King, Dr K Baillie
Application Deadline: 7 January 2019
Additional Supervisor. Dr Ian MacCormick. Background. The eye provides a window through which structural and functional characteristics of blood vessels can be visualised and quantified using new technology.
  Predicting the next global geomagnetic reversal using machine learning
  Dr P Livermore, Dr C Davies
Application Deadline: 7 January 2019
The Earth’s magnetic field, generated by turbulent convection in the liquid outer core, has reversed many times over its 3.5 billion-year history, at a present rate of about 2-3 times per million years (Stern, 2002) The last global reversal took place 780,000 years ago, leading to speculation that we are “overdue”.
  Fully funded PhD Scholarship - Machine learning and wearable activity recognition
  Dr D Roggen
Application Deadline: 31 December 2018
Wearable motion sensor data can be interpreted with AI and machine learning techniques to infer human activities and provide contextual assistance, for instance in a wearable fitness coach or for industrial or elderly assistance.
  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
  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.
  Combining machine learning and closed-loop control theory
  Prof A Parnell, Prof S Dey
Application Deadline: 4 January 2019
The successful student will work with Professor Andrew Parnell and Professor Subhra Dey’s research groups as part of the new SFI I-Form centre on analytics for advanced manufacturing.
  MRC Precision Medicine DTP: Using machine learning to dissect genetic effects on DNA methylation heterogeneity in cancer
  Research Group: MRC Human Genetics Unit
  Dr D Sproul:, Dr G Sanguinetti
Application Deadline: 7 January 2019
Background. Genetic and epigenetic heterogeneity are fundamental hallmarks of cancer. Advances in high-throughput sequencing have resulted in the extensive characterisation of intra-tumoural genetic heterogeneity.
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