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 Research Theme Leader in Theory, Modelling and Computation

Applications are invited for any suitable member of academic staff within a SICSA Institution to co-lead the SICSA Theory, Modelling and Computation Research Theme.

Role Purpose 

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.

The role of the SICSA Theme Leaders is to coordinate activities within each of the defined SICSA themes and further develop coherent communities in these areas.

For further information on the role and to apply, please download the guidelines and application form below.

Theme Leaders Role Description

Application Form_SICSA Theme Leaders

Closing Date: 31st May 2019

SICSA Director

Applications are invited from any suitable member of academic staff within a SICSA Institution for the role of SICSA Director.

Job Purpose
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.  The SICSA Director provides academic leadership for SICSA, working with the SICSA Directorate and the SICSA Executive. 

Main Responsibilities
The SICSA Director role is part-time, taking approximately 20% of the working week as follows:

Working with Directors and SICSA Executive to deliver activities such as research themes, researcher mobility, SICSA Graduate Academy, Knowledge Exchange and other events (10%)

Directing and Chairing the SICSA Committee, SICSA Research Committee and SICSA Advisory Board, interacting with SICSA constituent Schools. (2%)

Liaison with Scottish Funding Council (SFC) and other bodies relative to the strategic direction of SICSA.  Representing SICSA on various external boards. (2%)

Developing overall SICSA strategy with the other SICSA Directors in the areas of research, teaching and knowledge exchange. (3%)

Representing and presenting SICSA at events such as DemoFest, SICSA PhD Conference, and other external events. (2%)

Participate in the annual Performance & Development process for the SICSA Executive Officer. (<1%)

For further information on the role and to apply, please download the guidelines and application form below.

SICSA-Director-Job-Description

SICSA Director Application Form 

Closing Date: 30th April 2019

Post-Doctoral Research Associate/Fellow position in Computing Science on Data Systems

University of Glasgow, School of Computing Science
Position: Full time
Salary Range: £35,210 – £39,610 / £43,266 – £50,132
Closing Date for Applications: 18 April 2019

To make a leading contribution to the EPSRC funded project “Closed-Loop Data Science for Complex, Computationally- and Data-Intensive Analytics” coordinated by PI Prof. Roderick Murray-Smith, working with Dr Nikos Ntarmos (line manager) and Dr Christos Anagnostopoulos.
Specifically, the job requires expert knowledge in large scale distributed systems, (big) data management and processing systems, and resource management and scheduling in distributed environments. The work will involve working closely with the technical team at JP Morgan’s Glasgow office, and there will be opportunities during the project for internships at JP Morgan.
The successful candidate will also be expected to contribute to the formulation and submission of research publications and research proposals as well as help manage and direct this complex and challenging project as opportunities allow. 

For more information please see: https://www.jobs.ac.uk/job/BQZ341/research-associate-fellow.
For informal enquiries please contact Professor Rod Murray-Smith

Ph.D. scholarship (42 months, with stipend and fees for EU/UK citizens) on modelling and evaluating closed loop interactions in recommender systems.

University of Glasgow, School of Computing Science
Stipend: Funding is available to cover tuition fees for UK/EU applicants for 3.5 years, as well as paying a stipend at the Research Council rate (est. £14,999 for Session 2019-20).
Closing Date for Applications: 15 May 2019
Supervisor: Dr Craig Macdonald

Project Description

Machine learning techniques are widely used to address many recommendation scenarios – such as suggesting a movie to watch on (e.g.) Netflix, or recommending a point-of-interest to visit in a city, often by learning from historical user data. However, recommendation systems can be influenced by what users have already been recommended and thereafter viewed/visited, rather than what these systems might have found to be relevant of their own accord – for instance, Netflix might start to recommend movies that are already popular from its previous recommendations.

Such an effect can be described as a filter-bubble or a closed-loop feedback, and has been typically avoided through introducing novel or serendipitous recommendations into the suggestions. However, the alternative use of approaches originating from closed-loop theory, such as intermittent control, have not been systematically investigated within recommender systems.

This PhD will be focussed on applying ideas and techniques from closed-loop theory to state-of-the-art recommender systems. The candidate will investigate the modelling and deployment of closed-loop recommender systems using new neural networks architectures in comparison and along traditional matrix factorization and BPR-based recommenders. The evaluation of the resulting systems will be conducted using both public benchmarks in recommender systems as well as within the experimental pipeline of some of our data partners in the EPSRC Closed-Loop Data Science project.

The successful candidate will have a strong interest/background in recommender systems, machine learning, and/or information retrieval.

This Ph.D will take place within the EPSRC project “Closed-loop Data Science”, https://www.gla.ac.uk/schools/computing/research/researchsections/ida-section/closedloop/

Ph.D. scholarship (42 months, with stipend and fees for EU/UK citizens) on Reinforcement learning in closed-loop data science.

University of Glasgow, School of Computing Science
Stipend: Funding is available to cover tuition fees for UK/EU applicants for 3.5 years, as well as paying a stipend at the Research Council rate (estimated £14,999 for Session 2019-20).
Closing Date for Applications: 15 May 2019
Supervisors: Professor Rod Murray-Smith and Dr Bjorn Hensen

Project Description

This studentship will explore reinforcement learning techniques in closed-loop data science, as part of the £3M EPSRC project ‘Closed-Loop Data Science’. https://www.gla.ac.uk/schools/computing/research/researchsections/ida-section/closedloop/

Progress in sensing, computational power, storage and analytic tools has given us access to enormous amounts of complex data, which can inform us of better ways to manage our cities, run our companies or develop new medicines. However, the ’elephant in the room’ is that when we act on that data we change the world, potentially invalidating the older data. Similarly, when monitoring living cities or companies, we are not able to run clean experiments on them – we get data which is affected by the way they are run today, which limits our ability to model these complex systems. We need ways to run ongoing experiments on such complex systems. We also need to support human interactions with large and complex data sets. In this project we will look at the overlap between the challenge someone faces when coping with all the choices associated with booking a flight for a weekend away, and an expert running complex experiments in a laboratory.

Reinforcement learning is a key tool in adapting closed-loop system performance. The student will have the opportunity to apply techniques together with applications problems from our research collaborators, which include Amazon, Moodagent, Skyscanner, JP Morgan and Widex

PhD Scholarship (42 months with stipend and fees for EU/UK citizens) on Moodagent – Conversational Music Assistant

University of Glasgow, School of Computing Science
Stipend: Funding is available to cover tuition fees for UK/EU applicant for 3.5 years, as well as paying a stipend at the Research Council rate (estimated £14,999 for Session 2019-20).
Closing Date for Applications: 15 May 2019
Supervisors: Dr Jeff Dalton and Professor Roderick Murray-Smith

Project Description

Conversational AI interfaces are beginning to allow people to communicate naturally with computers for the first time. This PhD, in partnership with Moodagent, focuses on intelligent music agents. At a basic level, this involves research and development of task-based music agents to allow people to interact with music (playing music, creating playlists, searching for music, etc…). Further, the goal is the development of an ‘intelligent’ agent that can incorporate contextual recommendations (music for running, music for a beach party, etc…) in a conversational context. For example, the context may include multiple users interacting (to create a playlist for a party) and the agent may help mediate the interactions. Going deeper, the aim is to develop conversational music intelligence that allows an agent to not simply perform tasks, but to converse with an agent about music. Music is a personal and subjective topic that is often vaguely defined, which make conversation in this domain both natural as well as an important research challenge. The explanatory descriptions from conversations about music will be used to explore research on deeper language-based understanding of music in order to improve quality and explainability of music retrieval and recommendation systems. This PhD will explore conversational music interactions in a cross-cultural and multilingual environment with Moodagent users in Denmark and India and will study key differences for this new and emerging group of users.
The PhD will study state-of-the-art task-based agent systems, including those based on deep learning models and that utilize reinforcement (and transfer) learning to learn agent policies. The research will also cover knowledge representation and research on construction of subjective personal knowledge graphs from conversation. It will incorporate conversational recommendation in multi-dimensional contexts, including social context, possibly involving groups of users

Assistant Professor / Associate Professor in Computer Science

Heriot Watt University
Salary: £40,792 – £58,089
Closing Date for Applications: 12 May 2019
Informal Enquiries: Dr Mike Just

Role Description:
To celebrate our 2021 bicentenary of pioneering research we welcome applications for an outstanding Assistant or Associate Professor in Computer Science. We are currently undertaking a strategic expansion and we are particularly interested in exceptional applicants with expertise in the following areas: verification, computer security, and data science. We hope to hire multiple positions from this advertisement.

In verification and rigorous systems, our researchers develop a range of methods that improve the reliability and predictability of computer systems through the development and application of rigorous design, implementation and verification techniques. Our research is developing strong formal foundations, with a current focus on proof theory and type systems, and integrates these foundational techniques into the design, implementation and verification of computer systems, in particular distributed and high-assurance systems. We invite applicants with expertise and a strong publication record in one of the following: programming languages, semantics, static analysis, type systems, proof theory, verification, formal methods, distributed systems, and parallel computation.

In computer security, our researchers work across multiple areas of expertise. With rigorous systems for safety and security, we model system safety hazards, study program language security, and assess the security of blockchains and computer networks. With usable security, we investigate the impact of computer security on people, including current investigations on the use of games for developer-centred security, and the online safety of people with autism spectrum disorder. With data-driven security, we use data science and machine learning to study computer security, including current investigations that perform data matching and integration for crisis management, and use machine learning to protect networks from external hackers and insider threats. We invite applicants with expertise and a strong publication record in areas of research that complement or augment our current portfolio of activities.

In data science, our interdisciplinary researchers work across the whole data pipeline from improving data discoverability, interoperability, and reuse, to data analytics and visualisations. We work with a wide range of application domains from biomedical and life sciences, social sciences, mobile communications, crisis management, urban planning, and environmental protection. Our research covers data science, artificial intelligence, and machine learning, in diverse areas such as FAIRifying data, semantic web and knowledge representation, machine learning for knowledge graph generation, natural language processing and conversational AI. In both 2017 and 2018, our teams were finalists in the Amazon Alexa Prize competition. We have designed topic modelling of large datasets for developing research strategy and recently completed a spinout company, FarmHand, based on our data analytics and prediction research. We invite applicants with expertise and a strong publication record in areas of research that complement or augment our current portfolio of activities.

For more information on the position including the additional value of benefits provided by Heriot Watt University please visit the web-site: https://jobs.hw.ac.uk/OA_HTML/OA.jsp?OAFunc=IRC_VIS_VAC_DISPLAY&p_svid=22112&p_spid=1112032