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Postdoc position MADEin4 (V32.4171)

Postdoc position MADEin4

Postdoc position on deep learning on the topic of disentanglement of latent factors in high dimensional (sequential) data, for the simulation, analysis and design of complex physical and reliable industrial systems.
Position
(Post-doctoral) Researcher
Department(s)
Department of Mathematics & Computer Science
FTE
1,0
Date off
31/12/2019
Reference number
V32.4171

Job description

Deep neural network models of high dimensional data in a supervised learning setting can reach very high performance. Nevertheless, their applicability is still challenged by a number of drawbacks; their behavior is hard to interpret, it is hard to provide strong guarantees of generalization, it is hard to incorporate existing domain knowledge in their training process, and it is hard to apply in real contexts where data is noisy, corrupted or violating the i.i.d assumption.

Several topics related to these challenges are of specific interest for this Postdoc positions. Specifically, we are looking for candidates with an interest in studying:

  • Disentanglement of factors for high dimensional data, particularly sequential and time series
  • Stability in Deep Learning, modeling highly sensitive systems (i.e. which exhibit chaotic behavior)
  • Generative models for simulation of complex systems (e.g. physical processes, optimal control)
  • Geometric DL models of non-Euclidian data (e.g. graphs and manifolds)
  • Deep Metric Learning for capturing expert knowledge via psychometric measurements
  • Reliable machine learning in the presence of noisy, missing or corrupted data.

As part of your application portfolio, you are highly encouraged to submit a research statement on one of the listed topics or a topic that you believe will address the challenges stated above.

This position is funded by the MADEin4 European project targetting the design and validation of data driven methods and tools for metrology in semiconductor industry. The project is joined by ca. 40 industrial and academic partners from Europe.

The successful candidates are expected to:

  • perform scientific research in the domain described
  • publish results at (international) conferences
  • collaborate with other group and faculty members
  • collaborate with selected MADEin4 project partners, attend project meetings and report on results
  • assist with educational tasks (e.g. supervise Master students and internships)

Job requirements

  • You are a talented and enthusiastic young researcher.
  • You have experience with or a strong background in machine learning, statistics or stochastics. Preferably you finished a doctorate in Computer Science, (Applied) Mathematics, (Applied) Physics, Information Technologies, Electrical Engineering or Mechanical Engineering.
  • You have good programming skills and experience (Python is an asset).
  • You have good communicative skills and are eager to work as part of a research team.
  • You are creative and ambitious, hard-working and persistent.
  • You have good command of the English language (knowledge of Dutch is not required).

Conditions of employment

  • A full-time appointment for a period of 15 months at Eindhoven University of Technology (TU/e) with an intermediate evaluation after 1 year.
  • Gross monthly salary from € 2.709 to € 4.274 (depending on work experience).
  • A yearly holiday allowance of 8% as well as 8.3% end of the year allowance.
  • An attractive package of fringe benefits, including holiday and end-of-year allowance and excellent sport facilities.

Information and application

Questions about this position should be addressed to dr. V. Menkovski (v.menkovski[at]tue.nl) or dr. M. Holenderski (m.holenderski[at]tue.nl).

Your application must contain the following documents (all in English):

  • Cover letter (1 page max), which includes a motivation of your interest in the vacancy and an explanation of why you would fit well for the project;
  • An extensive curriculum vitae;
  • A course list of your Masters and Bachelor programs (including grades);
  • A summary of your PhD thesis;
  • Results of a recent English language test, or other evidence of your English language capabilities;
  • Name and contact information of two references.

If you are interested, we invite you to apply as soon as possible by using the ‘apply now’ button. You can upload one file including all the required documents (max. 10 MB).

We will start considering applications and interviewing immediately upon receiving an application.

Applications submitted by e-mail will not be considered.