Vacancies

SICSA continues to grow as a world-class pool of researchers in Informatics and Computing Science and there are a range of vacancies occurring regularly across the SICSA member Universities.

This page also features vacancies from industrial employers seeking to recruit graduates in Informatics and Computing Science.

Please note that all applications to external vacancies (outside SICSA) must be made directly to the advertising institution or organisation and not via SICSA


SICSA Education Director

Applications are invited for this post from any suitable member of academic staff within a SICSA Institution

Funding: The post is funded at £10K per year for 2 years (to be paid directly to the host institution)

Job Purpose and Background

SICSA is the Scottish Funding Council Research Pool in Informatics and Computer Science.  The goal of SICSA is to cohere the Scottish Informatics and Computer Science research communities to help increase critical mass and to enable cooperation in Research, Teaching and Knowledge Exchange.

Following discussion with SFC, SICSA’s remit was expanded in September 2011 to encompass Education, incorporating many of the activities of the informal Scottish Heads of Computing group.

SICSA Education has a focus on enhancing collaboration across the core activities of Undergraduate and Postgraduate education provision in Scotland. The group represents common interests to government; employers; professional and practitioner organisations; and the wider education sectors. These include resourcing for University Computing programmes, secondary school qualifications, the transition from school to University, and graduate skills.

If you wish to speak informally about the post, please telephone SICSA Director, Professor Kevin Hammond on +44 (0)1334 46 3241.

Applicants must complete an application form and submit to Steven.Kendrick@Glasgow.ac.uk by no later than Friday 1st December 2017.

Education Director Job Description

Application for the role of SICSA Education Director


Fully funded PhD in at Heriot Watt University: Online Safety & Autism “Protecting the online safety, security, and privacy of young people with special needs”

Project description
The goal of this project is to design effective tools to protect the online safety, security, and privacy of young people with special needs. Current approaches rely on carers (e.g., parents, grandparents, siblings) to use a combination of ad hoc procedures and technologies to protect of their children, such as “home rules” (e.g., limiting computer access, turning off wireless hub), and monitoring technology (e.g., net nanny). Recent research of carers of children with autism (Just & Berg, 2017) has shown that carers struggle to effectively and consistently protect their children, highlighting their own technical inadequacy, the limitations of current technology, as well as the wider gap between them and their high performing children. It is expected that the project will contribute in two areas. Firstly, it will provide an understanding of the key digital challenges faced by carers and their children, and will make use of a variety of data gathering techniques for this purpose (e.g., focus groups, field studies) by working closely with carer groups and special needs schools across Scotland and the UK. Secondly, it will involve the design and testing of educational approaches for assisting carers and their children, which may involve, for example, tools for assisting childrens’ interactions online via advice and nudging, and tools for more effectively automating carers’ “home rules”.

Please contact Dr Berg  if you are interested in this opportunity.

Supervisors
Dr. Tessa Berg and Dr. Mike Just

Funding details
A 3-year funded studentship to cover fees and a stipend is available for this project. Students must either be UK resident, which generally includes UK citizens and other EU citizens who have been resident in the UK for at least 3 years.

Related references
Just, M., & Berg, T. (2017, September). Keeping Children Safe Online: Understanding the Concerns of Carers of Children with Autism. In IFIP Conference on Human-Computer Interaction (pp. 34-53). Springer.
DOI: https://doi.org/10.1007/978-3-319-67687-6_3

 


Ph.D. vacancy in Machine learning for Novel Imaging Systems

University of Glasgow, supervised by Prof. Roderick Murray-Smith http://www.dcs.gla.ac.uk/~rod/  Available immediately, part-funded and run in collaboration with Amazon Research and QuantIC , the UK Quantum Technology Hub in Quantum Enhanced Imaging, https://quantic.ac.uk.

There will be opportunities for applying for  internships at Amazon’s labs in Cambridge, Berlin or Seattle during the Ph.D.

The project will use machine learning frameworks such as  Deep Convolutional networks and autoencoders with novel imaging techniques, including single-pixel cameras, hyperspectral imaging, 3D from ultra-precise timing and low-photon count imaging. The work will use novel imaging systems developed within the QuantIC hub.

The stipend funding is at standard UK rates (£14,553), and includes fees (only available for UK/EU citizens). Please apply by sending a c.v. to ASAP to Roderick.Murray-Smith@glasgow.ac.uk with the final deadline being the 10th December 2017. The successful candidate will be able to start immediately.


Funded PhD Scholarship to UK/EU applicants on Internet of Robotic Things for Connected Social Care

The School of Engineering and Physical Sciences (EPS) at Heriot-Watt University is offering full fees and stipend for a 3 year fully-funded PhD studentship to UK/EU applicants on Internet of Robotic Things for Connected Social Care.

The successful candidate will contribute to the development of innovative, user-friendly, interactive and modular IoT-Robotic systems that are able to understand and operate effectively and flexibly in people’s homes, to look after the safety and comfort of their users and assist them in their daily lives while also learning to smoothly adapt to their constantly evolving needs. These features can greatly simplify the design and customization of engaging and cost-effective systems while benefiting from technological trends to promote their adoption as part of personalised and connected social care practices that link homes with assisted care and health services.

The specific research will avail of a new laboratory part of an international network of “home lab” test-bed facilities.

The laboratory is a 60 square meter, fully sensorised smart robotic space equipped with state of the art domestic robots and smart home technology and with links to deep-learning and other computing resources. It provides a ‘Living Lab’ home environment where roboticists and computer scientists, and also usability and health experts, psychologists, and sociologists, can work alongside people with assisted living needs and those supporting them, to co-design and test innovative solutions for healthy ageing and assisted living.

The successful candidate is expected to hold a master or 1st class honours degree in robotics, computer science or a relevant discipline.
Previous experience and knowledge in human-robot interaction and artificial intelligence would be desirable.
Good interpersonal skills, communication, and collaboration capabilities will be an asset.
Applications should be made online at https://www.hw.ac.uk/study/apply/uk/postgraduate.htm
Required Documents: Completed online application form, CV, transcripts, 2 reference letters, and a cover letter to briefly state research interests and motivation.

Potential candidates are encouraged to send an inquiry email to Dr. Mauro Dragone (m.dragone@hw.ac.uk) if they wish to find out more about the position and discuss project ideas before applying.


Research Associate/Assistant in Networked Systems Research Lab (netlab)
University of Glasgow, School of Computing Science
Salary:  Salary (depending on qualifications): £28,098 to £38,833 per annum
Closing Date for Applications: 7th January 2018

We are looking for candidates with strong interest and experimental background in networked systems, especially in emerging technologies such as network function virtualisation and software-defined networking.

The post is funded by the UK Engineering and Physical Sciences Research Council (EPSRC) to work on the project ‘Network Measurement as a Service’, and funding is available until 31 October 2019 in the first instance.  for more information and application details please see:  http://www.jobs.ac.uk/job/BFV510/research-assistant-associate/


Funded PhD Studentship University of Glasgow

We will combine expertise in chemistry, spectroscopy, entomology, and computing science to apply state-of-the-art machine-learning techniques to the determination of traits in insects and the design of novel molecules for attracting or repelling insects.

In the battle against the spread of diseases such as malaria and Zika, it is critically important to be able to monitor the distribution of ages, species, and other traits of the population of vector species that transmit disease. As a simple example, malaria can only be transmitted by mosquitoes older than 10 days. Therefore, control efforts should focus on reducing the fraction of older mosquitoes. The current best methods for doing this are highly inaccurate or expensive.

We have been able to demonstrate in preliminary work on mosquitoes that the mid-infrared spectrum contains sufficient information to determine age and species when analysed using a simple neural network. In this project, much more complete and robust analysis will be developed using supervised machine learning using more extensive spectral data sets. We will use dimensionality-reduction techniques for gaining greater insight into what spectral data are most important, we will use different forms of data, and generate synthetic data to improve robustness. We will add near- infrared spectral data to allow the machine-learning algorithms to discover additional correlations. The experiments will be carried out on mosquitoes reared in Glasgow and at the Ifakara Health Institute in Tanzania as well as ticks from Scotland.

The initial work on application of machine learning tools in a fairly standard approach will give the student a firm foundation, preparing them for exciting advanced work on graph-convolutional autoencoders to produce a data-driven continuous representation of molecules. We already have a machine-learning model trained on a database of 500,000 SMILES representations of molecules from pubchem. Preliminary work has shown that the attractiveness of a molecule to mosquitoes can be quantified semi-automatically on a greatly parallel scale, which will be exploited to find novel molecules that repel or attract insects. This is a potentially disruptive technology with wide applicability to molecular design.

Project Team and where student will be based:

The project will be led by Prof Klaas Wynne in the School of Chemistry and co-supervised by Prof Roderick Murray-Smith in the School of Computing Science and Dr Francesco Baldini in the Institute of Biodiversity Animal Health and Comparative Medicine. The student will work among the three groups and primarily be based in Chemistry. The supervisors will hold regular meetings with the student to review the project’s progress and also to provide supports as required in order to meet the anticipated project goals in time. S/he will have access to the facilities available in three research groups and will also benefit from a highly active research culture of working in the interdisciplinary team.

Person Specification

This studentship is open to candidates of any nationality – UK, EU or International.
Applicants should demonstrate the following:

  • Academic qualifications
  • Experience
  • Skills/Attributes

Applicants should have a good degree in a relevant science discipline (e.g., physical chemistry, chemical physics, computing science), be highly motivated and have excellent English communication skills. The successful candidate will need to be enthusiastic about acquiring new skills and have an interest in spectroscopy and programming. Research experience, laboratory skills, experience with infrared spectroscopy, and familiarity of programing in Python will be considered an advantage.

In the first instance, prospective applicants should contact Prof Klaas Wynne (klaas.wynne@glasgow.ac.uk) to discuss their eligibility. Applicants may submit applications up until the application deadline of 12 noon, Friday 12 January 2018.

The following documentation will be required from applicants if they are invited to submit a full application:

  • Application form
  • 2 references in support of your application. (The references relevant to the application for admission to Glasgow for PhD study may be submitted to this process – they do not need to be tailored to this process.)
  • Degree transcripts in English (Undergraduate and Masters, if relevant)
  • Candidates whose first language is not English must show evidence of appropriate competence in English in the form of a IELTS certificate or similar.