[DMANET] Post doc position in theoretical computer science

There is an open 21 month post doc position at the Department of Computer Science Aarhus University. The start date is 01.04.2022 or after mutual agreement.

Application Deadline: 15 December 2021.

We are seeking candidates with strong interest and expertise in algorithm development in relation to a new project on developing tensor based algorithms for usage in chemistry using a combined computer science and theoretical chemistry perspective. The project will involve working in a focused team including Assoc. Prof. Kasper Green Larsen (Algorithms, Data Structures and Foundations of Machine Learning, Department of Computer Science, Aarhus University, https://cs.au.dk/research/algorithms-data-structures-and-foundations-of-machine-learning/), and Prof. Ove Christiansen (Theoretical Chemistry, Department of Chemistry, Aarhus University, homepage https://chem.au.dk/en/research/research-areas-and-research-groups/theoreticalchemistry/midas/) and two post docs. This is the job add for one of these postdoc positions. This team is embedded in the bigger Larsen and Christiansen groups at the computer science and chemistry departments at Aarhus University.

The ideal candidate has a Ph.D. degree in theoretical Computer Science, Chemistry, Physics, or related disciplines. Important background includes strong analytical abilities and expert programming skills. Collaborative skills are necessary as well as a high level of independence. Other key-words of notice are numerical linear algebra, sketching, dimensionality reduction, tensors, iterative algorithms. Previous experience with C++ programming will be considered an advantage.

The project team will develop, test, and apply methods for tensor decomposition. A key focus point is the CANDECOMP/PARAFAC (CP) decomposition. We will develop new and more efficient and accurate CP based algorithms that can have a large impact in theoretical chemical computations. One target is supporting efficient computation of energies, spectra, and wave functions for nuclear motion (https://doi.org/10.1063/1.5001569, https://doi.org/10.1063/5.0037240). Another focus point is the exploration of novel alternative tensor formats, their generalizations, and efficient algorithms. Finally, tensor decomposition as a tool for analysing experimental data will be considered.

A link to the application form can be found here:

https://www.au.dk/om/stillinger/job/postdoc-positions-in-theoretical-computer-science-at-aarhus-university


Best regards
Kasper Green Larsen

Associate Professor, Ph.D.
Head of Algorithms, Data Structures and
Foundations of Machine Learning
Computer Science
Aarhus University, Denmark

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