[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: rebh...@insight-centre.org<mailto:rebh...@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.mad...@nuigalway.ie<mailto:michael.mad...@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/

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