PhD project: Workflows for reproducible computational science and data science¶

Carrying out data analysis of scientific data obtained from simulation or experiments is a main activity in many research disciplines, and is essential to convert the obtained data into understanding, publications and impact. A topic that receives growing attention is that of reproducibility and re-usability: Given a publication, it should be possible for readers of the publication to reproduce the results published in the paper, particularly so if the results are based on computational processes. This forms the bases for re-use of the work, for example to extend the software to carry out a related but new study. In practice, this is often impossible.

In this project, we will investigate the process of computational science research, including computing simulation and data analysis towards publication, and will then work to improve this workflow. Challenges include to preserve all computation and processing steps, the specialist software, and its computation environment so that the computation can be reproduced and re-used in the future. Objectives are to make the process reproducible, convenient and effective.

Important tools for the technical part of this work are likely to include the Jupyter Notebook and ecosystem of tools, including Python, and package managers such as Spack, and containers.

We are looking for a computational scientist with a background in physics, chemistry, mathematics, engineering or similar with strong interest in programming and computational science, or for a computer scientist with interest in supporting computational science.

The project is listed on https://www.dashh.org/application/phd_topics/index_eng.html

Supervisory team¶

Requirements¶

Degree in Physics, Computer Science or a related field
Programming experience (any language)
English is the working language, hence good communication skills in English are necessary
ideally experience with at least some libraries and tools from the scientific computing Python ecosystem such as Jupyter, IPython, numpy, scipy, matplotlib, pandas, ploty, bokeh, …

Desirables¶

experience with computational science, data analysis, High Performance Computing would be welcome

Contact¶

For additional information, please do not hesitate to Hans Fangohr (hans.fangohr@mpsd.mpg.de).

Primary working place will be the Max Planck institute for Structure and Dynamics of matter (MPSD) on DESY Campus in Hamburg.

Context¶

The work will be carried out in a multidisciplinary environment bringing together natural sciences and computer science, and with the desire to support computational research at the Max-Planck Institute for Structure and Dynamics of Matter and the Deutsches Klimarechenzentrum . Our ambition would be to advance the best-practice in the area of reproducibility and re-usability that can be applied outside these research communities as well. We will also work with Michael Kuhn from the Parallel Computing and I/O group at Otto von Guericke University Magdeburg.

Deadline and timeline¶

The deadline for applications to be received is 1 December 2020

The timeline after submission is roughly as follows:

There will be a selection workshop in Hamburg for shortlisted candidates early in 2021
Candidates are expected to receive a decision by March 2021
Earliest start of the PhD project is likely to be May 2021. There is some flexibility regarding a later start date.

Application¶

Please see https://www.dashh.org/application/application_procedure/index_eng.html, and get in touch with Hans Fangohr (hans.fangohr@mpsd.mpg.de).