From: Torben Bach Pedersen <email@example.com>
Date: Thu, Mar 15, 2012 at 7:47 PM
Subject: [Dbworld] Ph.D. positions at Aalborg University
A number of fully funded Ph.D. positions are available at the Center for Data-intensive Systems (Daisy),
Department of Computer Science, Aalborg University (AAU), Denmark.
The positions are available from August 1, 2012, or as soon as possible thereafter.
The positions are related to the TotalFlex smart grid project sponsored by Energinet.dk
The aim of the project is to develop IT technologies that help accomodate larger fractions of renewable energy into the
energy production by building an integrated solution for managing flexible energy consumption,
so-called “demand response.”
The vision of TotalFlex is to develop a cost-effective, market-based system that utilizes total
flexibility in energy demand and production, taking balance and grid constraints into account.
The approach is based on the flex-offer concept pioneered by the EU FP7 project Mirabel http://www.mirabel-project.eu
Flex-offers express an intent to use energy in a flexible way, e.g., for operating a dishwasher, a consumer
could issue the flex-offer “I need 1KWh over 1.5 hours between 10PM and 7AM and I will pay
0.30DKK/KWh for it.”
Applications are invited on the following research topics:
A) Flexibility detection and prediction: It is possible to automatically and precisely
detect and predict energy consumption, production, and flexibility at the device level and use
the predictions to automatically generate (potential) flex-offers. This can be realized by applying
data mining and machine learning techniques to the data, coupled with taking the concrete use
context and the historical behaviour of the users into account. The prediction of flexibilities is an
interesting general research problem.
B) Data aggregation and analysis: It is possible to efficiently aggregate
and analyse large amounts of complex energy-related data such as flex-offers over multiple
domain-related perspectives (dimensions) to benefit all energy market actors simultaneously.
This can be realized by building a multidimensional data warehouse for capturing and querying
the data and developing new techniques for aggregating over complex dimensions structures. In
particular, aggregating over complex spatial structures with associated physical constraints
(network grid) is an interesting research challenge.
Applicants must have a master degree in computer science or a closely related field, with very good grades.
They are expected to have good knowledge of databases (preferably multidimensional databases), data warehousing, and/or data mining,
as well as strong implementation skills. Good communication skills in English, oral as well as written, are essential.
More information about Daisy can be found at http://daisy.aau.dk/.
For further information about the technical aspects, please contact:
Professor Torben Bach Pedersen (tbp AT cs DOT aau DOTdk)
Please follow the online application procedure (link given below) carefully, applications via email are NOT considered.
Link to online application: http://tinyurl.com/7ff2l97
Applicants must submit the following material through the online application system:
1) Full CV
2) Diplomas and grade transcripts for both bachelor and master studies.
3) A 2-3 page proposal for the Ph.D. study plan, aimed SPECIFICALLY at one of the topics A or B.
The proposal should have the following sections: Background and Motivation, Proposed Research,
Expected Results, Time Schedule, and References.
4) Documentation of English proficiency, i.e., scores for TOEFL or similar tests.
5) Other material, e.g., copies of a few relevant publications (if applicable).
— General info regarding Ph.D. studies at AAU
Danish universities offer very high Ph.D. salaries (and good social benefits) that compare very well with the rest of the world.
The monthly pre-tax salary at AAU is approximately DKK 26,000, plus DKK 2,600 pension contribution. In order to broaden their research horizons, Ph.D. candidates at
AAU are also financially supported for a one-semester academic visit to international universities/institutions.
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