As part of the Science of Sensor Systems Software programme we have a 3-year postdoc post available.
The S4 programme aims to develop a unifying science, across the breadth of mathematics, computer science and engineering, that will let developers engineer for the uncertainty and ensure that their systems and the information they provide is resilient, responsive, reliable, statistically sound and robust. The vision is smarter sensor based systems in which scientists and policy makers can ask deeper questions and be confident in obtaining reliable answers, so the programme will deliver new principles and techniques for the development and deployment of verifiable, reliable, autonomous sensor systems that operate in uncertain, multiple and multi-scale environments.
S4 is funded by EPSRC as a five-year, £5.2M Programme Grant. It brings together four of the UK’s leading research teams in sensor systems, their design, analysis, deployment, and evaluation. Led overall by Prof Muffy Calder at the University of Glasgow, the other academic collaborators are the University of St Andrews (Prof Simon Dobson), the University of Liverpool (Prof Michael Fisher), and Imperial College (Prof Julie McCann). S4 also includes a portfolio of industrial partners ranging from start-up SMEs to multinational companies and State agencies.
St Andrews leads the work on adaptive systems engineering, especially on how systems need to change as time progresses, the system components fail, and goals change. We are looking for someone to join us to work on how to program adaptive sensor systems. A strong track record in sensor systems, programming languages, data analytics, or another related area is essential, as is an ability to work within a larger team using formal methods, advanced statistics, and novel programming languages and approaches
You can find full application details here.
SASO 2017 is now accepting paper submissions. Come and join us in Arizona!
Aims and ScopeThe aim of the Self-Adaptive and Self-Organizing Systems conference series (SASO) is to provide a forum for the presentation and discussion of research on the foundations of engineered systems that self-adapt and self-organize. The complexity of current and emerging networks, software, and services can be characterized by issues such as scale, heterogeneity, openness, and dynamics in the environment. This has led the software engineering, distributed systems, and management communities to look for inspiration in diverse fields (e.g., complex systems, control theory, artificial intelligence, chemistry, psychology, sociology, and biology) to find new ways of designing and managing such computing systems in a principled way. In this endeavor, self-organization and self-adaptation have emerged as two promising interrelated approaches. They form the basis for many other so-called self-* properties, such as self-configuration, self-healing, or self-optimization. SASO aims to be an interdisciplinary meeting, where contributions from participants with different backgrounds leads to the fostering of a cross-pollination of ideas, and where innovative theories, frameworks, methodologies, tools, and applications can emerge. The eleventh edition of the SASO conference embraces this inter-disciplinary nature, and welcomes novel contributions to both the foundational and application-focused dimensions of self-adaptive and self-organizing systems research. The topics of interest include, but are not limited to:
- Systems theory: nature-inspired and socially-inspired paradigms and heuristics; inter-operation of self-* mechanisms; theoretical frameworks and models; control theory;
- System properties: robustness; resilience; stability; anti-fragility; diversity; self-reference and reflection; emergent behavior; computational awareness and self-awareness;
- Systems engineering: reusable mechanisms and algorithms; design patterns; architectures; methodologies; software and middleware development frameworks and methods; platforms and toolkits; multi-agent systems;
- Theory and practice of organization: self-governance, change management, electronic institutions, distributed consensus, commons, knowledge management, and the general use of rules, policies, etc. in self-* systems
- Theory and practice of adaptation: mechanisms for adaptation, including evolution, logic, learning; adaptability, plasticity, flexibility
- Socio-technical systems: human and social factors; visualization; crowdsourcing and collective awareness; humans-in-the-loop; ethics and humanities in self-* systems;
- Data-driven approaches: data mining; machine learning; data science and other statistical techniques to analyze, understand, and manage behavior of complex systems;
- Self-adaptive and self-organizing hardware: self-* materials; self-construction; reconfigurable hardware;
- Education: experience reports; curricula; innovative course concepts; methodological aspects of self-* systems education;
- Applications and experiences with self-* systems in any of the following domains are of particular interest:
- Smart systems: smart grids, smart cities, smart environments, smart homes, etc.
- Industrial automation: embedded self-* systems, adaptive industrial plants, Industry 4.0, cyber physical systems
- Transportation: autonomous vehicles, traffic optimization
- Autonomous systems: aerial vehicles, undersea vehicles, autonomous robotics
- Internet of Things: self-* for network management, self-* applied to cyber security
|Abstract submission||May 1, 2017|
|Paper submission||May 10, 2017|
|Notification||June 30, 2017|
|Camera ready copy due||July 12, 2017|
|Conference||September 18-22, 2017|