PhD Position in model-driven data analytics (for the biomedical domain)

[Apologies for cross-posting]

PhD Position in model-driven data analytics (for the biomedical domain)
Mathematical models for biomedical data are a powerful means to infer complex mechanisms from experimental data.  Such models are applied to infer regulatory networks from experimental data for cells, but also for the assignment of functional states cells and tissues derived from experimental time series.
The healthcare and Life Sciences (HCLS) domains are developing into data driven sciences, which gather and contribute the public biomedical knowledge in standardized representations throughout the world. Increasingly semantic Web technologies are being applied in these knowledge rich domains to achieve interoperability of data and the semantic normalisation of the data resources for subsequent interpretation.  This data is available as an integrated knowledge graph to contribute to the prior knowledge in the mathematical model, but also serves as a validation infrastructure, since the known knowledge should be replicated through the mathematical model.
Expert knowledge in the form of mathematical models can be considered sufficient statistics of prior experimentation in the domain, embodying abstract knowledge of it. When used in a probabilistic framework, such models provide a sound foundation for data mining, inference, and decision making under uncertainty.
The PhD position will focus on new analytical methods in the biomedical domain that can exploit both the knowledge graph and relevant mathematical models, with application to the prediction of states for cells, tissues and more complex regulatory processes. The prior knowledge results from publicly available data in terms of network information, but also on assumptions on the underlying mechanisms and complex semantic annotations for the involved components. Part of the research work is the participation into public challenges and the analysis of standard data sets for the prediction of the known states. Particular focus will be set on the molecular and phenotypic characterisation of cellular, tissues and other organismal states based on the full integration of the biomedical knowledge graph for particular diseases.

The Insight Centre for Data Analytics and the Information Technology Discipline at the National University of Ireland, Galway, invite applications for a PhD position in the area of mathematical modelling, machine learning, statistical models, and development of prediction models. The PhD student will be hosted by the Information Technology discipline in the National University of Ireland in Galway (NUIG) and the Insight Institute at NUIG. The selected candidate will be embedded in international collaborations and possibly also European research projects. The candidate will be enabled to publish in high impact international conferences and journals and to participate in world leading research.


Eligibility

*        Four Years Bachelor's Degree or Master's Degree in Computer Science, Statistics, Applied Mathematics, Data Analytics, Operations Research, Information Technology, or Bioinformatics

*        Good knowledge of data analytics principles, for example machine learning, data mining, and/or statistics for data analysis

*        Good background in Java, Python or R programming

*        Strong interest in building mathematical models for prediction

*        Alternative skills: semantic web technologies, knowledge graphs


Stipend: PhD scholarship stipend of 18,000 per year, no tax. The duration of the contract will be 4 years as a fully funded PhD.


Application procedure
 Informal enquiries about these positions may be made to:
Prof. Dr. Dietrich Rebholz-Schuhmann
Insight Centre for Data Analytics

NUI Galway, The DERI building

IDA Business Park, Lower Dangan

Galway, IRELAND

Email: rebholz@insight-centre.org<mailto:rebholz@insight-centre.org>

Dr. Michael Madden

Machine Learning & Data Mining Research Group,
College of Engineering & Informatics

National University of Ireland, Galway

Galway, IRELAND

Email: michael.madden@nuigalway.ie<mailto:michael.madden@nuigalway.ie>


When applying, please use the same email addresses above and put " PhD Position in data modelling and simulation" in the subject line of your email. Candidates are requested to submit (1) a cover letter explaining your intentions, and (2) a CV (in PDF format) giving details on your academic degrees, working experiences and IT skills (maximum 2 pages). It is difficult but still advantageous, if you can write a paragraph (e.g. in the cover letter, or extra), what ambitions in the PhD position appeal most to you.

Interviews will be carried out towards middle and end of October via skype conference call, and the position can be filled without much delay if required. We expect the successful candidate to start at the earliest possible date, ideally towards December 2015.



INSIGHT Centre for Data Analytics (previously DERI http://deri.ie/) http://www.insight-centre.org/ is a leading research institute in Semantic Web/Linked Data technologies that offers a stimulating, dynamic and multi-cultural research environment, excellent ties to research-groups worldwide, close collaboration with industrial partners and up-to-date infrastructure and resources.

The Information Technology Discipline (http://www.it.nuigalway.ie/) is NUI Galway's Computer Science department and has a 20-year track record in innovative teaching, research, and engagement with industry and community. It is the largest academic discipline in the College of Engineering & Informatics, and has an established track record of excellence in research and technology development, leading to numerous successful research groups with research ranging from theoretical advances to applications in science, engineering, business, and medicine.

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Regards,

Ratnesh Sahay, PhD

Research Unit Leader

Semantics in eHealth and Life Sciences (SeLS)

Insight Centre for Data Analytics

NUI Galway, The DERI building

IDA Business Park, Lower Dangan

Galway, IRELAND

Tel: + 353 91 495253

Fax: + 353 91 495541

Web: http://sels.insight-centre.org/
Web: http://www.ratneshsahay.org/