Open PhD Positions

A number of PhD research projects have been selected for funding through the last call of the Microsoft PhD Scholarship Programme. For some of these projects, PhD supervisors are seeking suitable students. The research projects listed on this page are currently accepting applications from PhD students.


Computational Algorithms as Biological Regulatory Networks

Primary supervisor: Attila Csikasz-Nagy, King's College London
Microsoft Research supervisor: Luca Cardelli
PhD expected start date: 1 October 2014

Summary: Evolution selected for biological network designs that are capable of fast and proper responses to inputs. Computing is also designed to handle tasks in a fast and precise way. The efficiency of biological systems is often copied when designing biologically inspired tools (evolutionary algorithms, machine learning, and so forth). The supervisor of this project, in collaboration with Luca Cardelli, investigated the similarities between a cell cycle regulatory switch and the Approximate Majority (AM) algorithm of distributed computing. The AM algorithm computes the majority of two finite populations and the cell cycle switch ensures that cells divide only after DNA replication is finished. The functions of the two switches differ but their dynamical behaviour is similar. The project goes further to investigate how biological regulatory systems can be converted to computational algorithms and how algorithms can provide us hints about non-clearly understood biological systems. Read a related publication: The Cell Cycle Switch Computes Approximate Majority

An MSc or in rare cases a BSc in Computer Science/ Bioinformatics/Biology/Physics/Applied Mathematics or related fields is required. For candidates coming from more computing or theory, an extensive knowledge of biology is required. For candidates coming from a biology background, we require excellent analytical and programming experience.

For further details, contact: or visit  Microsoft Research PhD scholarship on Computational Algorithms as Biological Regulatory Network.

Also, see PhD studentship opportunities.

Posted: 9 April 2014

Verifying Concurrent Higher-Order Programs

Primary supervisor: Matthew Hague, Royal Holloway UoL
Microsoft Research supervisor: Andrey Rybalchenko
Application deadline: 31 May 2014
PhD expected start date: The studentship will start in or after October 2014.

Summary: Higher-order programming features are increasingly supported by modern languages, such as F Sharp, Python, Scala, Haskell, OCaml, and C++. Thus, this forms an increasingly essential topic for verification for which there have been several important recent advances. Furthermore, it is clear that concurrency will become the dominant programming paradigm, due to both the ubiquity of multi- and many-core machines and the increasingly distributed nature of computation, especially in the processing of "Big Data."

Current verification tools for higher-order programs tend to focus on non-concurrent programs. During this PhD, you will survey the existing state of the art analysis techniques for higher-order programs and develop new techniques and tools based on one of these approaches for analyzing concurrent higher-order programs.

To apply, please contact Matthew Hague directly by 31 May 2014.

Posted: 26 March 2014

Reasoning About Side Channels in Cryptographic Protocols

Primary supervisor: Boris Köpf, IMDEA Software Institute, Spain
Microsoft Research supervisor: Cédric Fournet
Application deadline:
Until the position is filled
PhD expected start date: Fall 2014

Summary: Side-channel attacks break cryptosystems by exploiting signals that are unwittingly emitted by their implementations. Many defense mechanisms rely on the context in which a cryptographic primitive is used; that is, the protocol. In the course of this project, we will devise techniques that enable reasoning about side-channel leakage in cryptographic protocols. The promise of our approach is to achieve high degrees of security and performance at the same time. To this end, we will tackle two open challenges: first, how to do compositional reasoning about leakage and its aggregation; second, how to embed low-level binary analysis into this compositional context.

To apply, please contact Boris Köpf or Cédric Fournet directly.

Posted: 26 March 2014

Sketching Algorithms for Massive Graphs and Matrices

Primary supervisor: Prof. Graham Cormode, University of Warwick, UK
Microsoft Research supervisor: Dr. Milan Vojnovic
Application deadline:
There is no final deadline, but applications received before the end of May 2014 will have the greatest chance of success.
PhD expected start date: The planned start date is October 2014, but January 2015 is also possible.

Summary: Increasingly, we are faced with larger and larger volumes of data from which to extract insights and intelligence. An important case surrounds data that can be represented as a graph or (adjacency) matrix. A promising approach is to look for ways to “sketch” such structures: to build a representation that is much more compact than the input, but which allows some function of interest on the original data to be approximated accurately by using the sketch. Such sketches are well known and widely used for data that can be represented as a vector (such as to identify the most frequent elements, or to count the number of distinct items). The goal of this scholarship project is to develop new algorithms for sketching massive graphs and matrices, and to demonstrate their usefulness via theoretical analysis and empirical evaluation.

To apply, please contact Graham Cormode or Milan Vojnovic directly.

Posted: 12 March 2014

GeoGraph: Efficient geographically distributed graph infrastructure

Primary supervisor: Prof. Fernando Pedone, University of Lugano, Switzerland
Microsoft Research supervisor: Dr. Flavio Junqueira
Application deadline: until the position is filled
PhD expected start date: summer (northern hemisphere) 2014

Summary: Many current online services build on graph data structures. Services in this category, which include social networks, collaborative applications, and recommendation systems, share a number of common characteristics. They typically serve a large user base, possibly geographically distributed; the underlying graph structure has particular properties (such as power-law distributions); users can tolerate certain anomalies (for example, non-serializable behavior) but expect some guarantees from the system (such as preserving causal dependencies among requests and availability in the event of failures and disasters); and most requests are either small graph updates (for example, inserting an edge between two vertices) or relatively large queries (for example, computing a user’s timeline in the case of a social network application). The goal of this project is two-fold: first, we aim to propose consistency criteria well adapted to graph-dependent online services. In this sense, consistency must account for the typical operations performed on graphs by online services. Second, we intend to design, implement, and experimentally assess an infrastructure that implements this isolation level (or levels).

To apply, send your CV and a research statement to Fernando Pedone (fernando.pedone at or Flavio Junqueira (fpj at, and arrange for two reference letters to be sent to the same email addresses. We’re happy to provide further information on request.

Posted: 6 March 2014

Approximate Bayesian Inference for Data Pipelines

Supervisors: Dr Iain Murray
Microsoft Research supervisor: Dr John Winn
Application deadline: until the position is filled
PhD expected start date: September 2014

Summary: Bayesian inference is rarely used coherently across all states of data processing in large-scale machine learning applications. Early stages of a pipeline are often seen as “pre-processing”, not part of a statistical model, and model criticism is usually also a separate manual stage. We aim to provide tools that allow more steps of processing to be routinely part of probabilistic analyses. Our plan is to develop new Monte Carlo fitting methods, resulting in more accurate and trustworthy results for a variety of data-processing tasks involving pipelines. Successful proof-of-concepts will be developed into general tools. Where appropriate, we will extend the Microsoft Research Infer.NET project, in collaboration with John Winn.

We are seeking to award a Microsoft PhD Scholarship on the topic of Approximate Bayesian inference for data pipelines.

The PhD scholarship is fully funded for three years. The project will be supervised by Dr Iain Murray of the School of Informatics at the University of Edinburgh, in collaboration with Dr John Winn at Microsoft Research Cambridge.

Posted: 10 February 2014 

Provenance for Configuration Language Security

Supervisors: James Cheney and Paul Anderson
Microsoft Research supervisor:
Dimitrios Vytiniotis
Application deadline: until the position is filled
PhD expected start date: Autumn (northern hemisphere) 2014

Summary: Declarative, high-level configuration languages are widely used in industry to configure large system installations. Configurations are often composed from distributed source files managed by many different users within different system and organisational boundaries. Users may make changes whose consequences are not easy to understand, and such systems also currently lack mature security access controls; the few currently available techniques have idiosyncratic behaviour and offer no formal guarantees. In the worst case, misconfiguration can lead to costly system failures; because of the complexity of the configuration build, it is difficult to recover from failures, trace the source of the error or identify the responsible party.

In this project, we will explore the application of provenance techniques (originally developed in the context of databases) to establishing well-founded and effective techniques for security and audit for configuration languages.

Posted: 22 January 2014