Scholarships and funding

You will gain skills in bioinformatics, statistics, machine-learning and drug design, alongside broader transferable research skills; producing a highly employable postdoctoral researcher, with a range of multidisciplinary skills.

Lead department: School of Biological Sciences (in collaboration with the School of Computer Science and Electronic Engineering)

Closing date: 7 May

This project aims to bringing together revenue management (demand scheduling) and vehicle routing models to minimize emission by means of giving incentives to encourage customers to choose least emission time windows. It will also provide resolutions on the efficient usage of electric fleets in grocery delivery.

Lead department: Department of Mathematical Sciences (in collaboration with the School of Computer Science and Electronic Engineering)

Closing date: 7 May

This studentship will research and develop a new neuro-adaptive learning environment for mathematical education. The information technology (IT)-based learning environment will adapt the learning content based on the learner’s task performance and brain signals (electroencephalogram (EEG)).

Lead department: School of Computer Science and Electronic Engineering (in collaboration with the Department of Psychology, and the Department of Mathematical Sciences)

Closing date: 7 May

We are looking for a highly motivated and interdisciplinary minded student, who has an excellent computer science, bioinformatics, electronics or related UG/MSc degree and is keen to work on relevant research in the area of design deep learning architectures and algorithms for age prediction based on DNA methylation data.

Lead department: School of Computer Science and Electronic Engineering (in collaboration with the School of Biological Sciences)

Closing date: 7 May

The successful applicant will (1) investigate the influence of the tonic experience of pain on neurophysiological markers extracted from the EEG, and (2) implement the detection of the neurophysiological markers of pain in a signal processing pipeline, based on brain-computer interface (BCI) technology that can be deployed at the bedside, for the online detection of pain.

Lead department: School of Computer Science and Electronic Engineering (in collaboration with the Department of Psychology)

Closing date: 7 May

The goal of the PhD studentship is to develop novel text analytics methods based on modern Deep Neural Networks. The novel text analytics methods will be applied to better understand and analyse the complexity of real-world activities and dynamics in socio-economic systems such as stock markets, health care services, innovation processes and others.

Lead department: School of Computer Science and Electronic Engineering (in collaboration with the Department of Mathematical Sciences)

Closing date: 7 May

This project is concerned with issues around data privacy in relation to the sharing of healthcare patient information/signal.

Lead department: School of Computer Science and Electronic Engineering (in collaboration with the School of Health and Social Care).

Closing date: 31 May 2019

The main motivation of this project is the need for an effective post-stroke rehabilitation system that provides provide 24/7 assistance to stroke survivors as well as healthcare providers at home or in hospital environments.

Lead department: School of Computer Science and Electronic Engineering (in collaboration with the School of Sport, Rehabilitation and Exercise Sciences).

Closing date: 31 May 2019

For the next level of robot intelligence, maps need to extend beyond geometry and appearance — they need to contain semantics. The inclusion of rich semantic information within a dense map enables a much greater range of functionality than geometry alone.

The PhD student will be investigating how knowledge from visual SLAM and machine-learned labelling can be brought together to enable powerful semantic and object-aware mapping in extreme environments.

Contact: Professor Klaus McDonald-Maier (kdm@essex.ac.uk) and Dr Shoaib Ehsan (sehsan@essex.ac.uk)

Closing date: 17 May 2019

It is expected that shortlisted candidates will be invited to attend interviews on 3 June 2019.

Please note that you need to apply for a PhD course through the university online portal, and fill out the department application form. More information can be found in the "Robot vision studentship" document below.