[DMANET] Two PhD Scholarships in Continuous-time Models for Machine Learning

Two PhD Scholarships in Continuous-time Models for Machine Learning at
Aalborg University, Denmark


We are looking for two highly motivated PhD candidates with interests in
continuous-time models, machine learning and optimization. The ideal
candidates will have a strong MSc degree in computer science,
mathematics or control engineering. The PhD scholarships are for three
years and come with a competitive salary and light teaching load.

Topic and qualifications: The envisaged research will focus on efficient
analysis of continuous-time models by means of dimensionality/model
reduction. The candidates are therefore required to demonstrate a strong
background and understanding in at least one of the following areas:

--- Continuous-time models such as Markov chains or differential equations
--- Mathematical optimization and dimensionality/model reduction
--- Scientific computing and software development

The envisaged starting date is October 2021, application deadline is the
6th of August. Fluent written and verbal communication skills in English
are required. Knowledge of Danish is not compulsory.

Application and contact: Applicants must have obtained a Master degree
before the appointment day. In addition to an academic CV and 2-3
reference letters, applicants should provide a short cover letter which
describes their background, research interests and initial thoughts and
ideas. Applications have to be submitted via:

https://www.stillinger.aau.dk/vis-stilling/?vacancy=1155031

For further information concerning the positions can be obtained via
tschaikowski@cs.aau.dk


Host institution: The Computer Science Department at Aalborg University
takes a leading international position within data management and
verification. Denmark in general and Aalborg in particular are known for
their excellent quality of life. Denmark took the top spot on the United
Nation's World Happiness Report, 2013 & 2014 & 2016 and came in third in
the 2015 report: http://www.https://www.visitdenmark.com/

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