Навигација
ViberX logo

Прилог Microsoft Research центра Cambridge

Стипендије и програмиУниверзитет у Бањој Луци

Postovani,
U prilogu Vam saljem informacije o dostupnim pozicijama za PhD studente u Microsoft Research centru Cambridge 
 
 
We have recently offered sponsorships to a number of researchers in EMEA so they can hire a PhD student to work with them and an MSR Cambridge researcher. These academic researchers are now looking for PhD students to come and study with them. Most positions are advertised here:
http://research.microsoft.com/en-us/collaboration/global/open-phd-positions.aspx
 
3 positions are specifically for students from India, China, Hong Kong, South Africa, Brazil, Russia and the developing world, as defined by the Development Assistance Committee of the OECD. The full list of eligible nationalities is at http://www.oecd.org/dataoecd/62/48/41655745.pdf + Russia and Hong Kong.
 
Feel free to advertise to students (with a first class degree and ready to embark on a PhD) in your region.
 
The above mentioned positions are:
http://research.microsoft.com/en-us/collaboration/global/open-phd-positions.aspx#computational_capabilities
http://research.microsoft.com/en-us/collaboration/global/open-phd-positions.aspx#digital_navigation
http://research.microsoft.com/en-us/collaboration/global/open-phd-positions.aspx#asthma
Computational Capabilities and Underlying Mechanisms in Biological Signaling Networks
Supervisor: Dr Orkun S. Soyer, University of Exeter
Microsoft Research Supervisor: Luca Cardelli
To apply: Please visit http://www.secam.ex.ac.uk/index.php?nav=newsArchive&nid=1541
This is a Dorothy Hodgkin Postgraduate Award (DHPA). Conditions apply on the nationality of the student; please visit the DHPA web site for the list of eligible nationalities.
Summary: Cellular communication and information processing are central to life. Such information processing requires coordinated interaction of multiple proteins that form a so-called signaling cascade or network. Achieving an understanding of dynamics in these signaling networks is one of the main aims of systems biology. Besides the obvious scientific value, this aim also connects directly to our understanding and treatment of diseases, as most disease conditions involve malfunction of signaling networks or their exploitation by pathogens.
The main aim of the proposed research is to analyze the relation between topological and biochemical features in signaling systems and response dynamics. The research strategy will involve building both detailed models of specific systems and generic models based on first-principles. Once such models are constructed we will be in a position to exhaustively analyze the repertoire of response dynamics in these systems and effectively map out their signal processing capabilities. Further, such models will allow us to analyze how different evolutionary processes can shape key features of signaling networks and generate novel information processing capabilities.
This project involves both theoretical and experimental skills/knowledge. In particular, a good grasp of biochemistry of signaling networks and molecular evolution, agent-based modeling, and system dynamics analyses (e.g., bifurcation analysis). The successful candidate should have an undergraduate degree (equivalent of class 2.1 or better for UK), with either a mathematical or a biochemical focus. Further, he/she should be motivated in expanding their skill set and working at the interface of microbiology, evolutionary biology, and computational/mathematical biology.
Are We Nearly There Yet? A Proposal to Explore Digital Navigation
Supervisors: ·    Dr Jon Rogers, University of Dundee
·    Dr Chris Speed, Edinburgh College of Art
Microsoft Research Supervisor: Richard Banks
This is a Dorothy Hodgkin Postgraduate Award (DHPA). Conditions apply on the nationality of the student; please visit the DHPA web site for the list of eligible nationalities.
To apply: Please send your CV to Jon Rogers and copy Chris Speed
Summary: The way we navigate has changed, and so too has the way in which we understand the context and environments: the roads, streets, and highways across which we travel. Digital technology is starting to alter the way we plan to get about, how we navigate getting about and the way we get back from getting about. From personal, to private, to public, to group travel - we are starting to do this differently and this may be the start of a cultural shift in the business of navigation. Understanding the social implications for these technologies is vital if we are to design better products to help people navigate the landscapes of the present and the future. We aim to investigate the future of navigation that focuses on the domestic routines of people in their homes, their neighbourhoods, in their relationships and in their landscapes.
Probablistic Causal Models for Asthma and Allergies Developing in Childhood
Supervisor: Prof. Iain Buchan, University of Manchester
Microsoft Research Supervisor: Christopher Bishop
This is a Dorothy Hodgkin Postgraduate Award (DHPA). Conditions apply on the nationality of the student; please visit the DHPA web site for the list of eligible nationalities.
To apply: Please send your CV to Iain Buchan
Summary: This trans-disciplinary PhD will focus on the exploitation of Bayesian machine learning methods, based on probabilistic graphical models, in the quest to understand the determinants of asthma and allergies from childhood, including the interactions between genetic and carefully-measured environmental factors. Structured Bayesian models will be built and solved using the Infer.NET library, and will be evaluated alongside conventional bio-statistical methods, such as multi-level models. The ultimate goal of the project is to elucidate realistically-complex causal networks of genetic and environmental factors responsible for asthma and allergies that develop in childhood. An allied PhD project will take a graphical model approach to studying the factors that determine the outcomes of treating type 2 diabetes. This will use the same type of genetic data and Infer.NET.