2 Research Assistants (m/f/d)
| Published | January 28, 2023 |
| Location | Kassel, Germany |
| Category | Machine Learning |
| Job Type | Scholarship |
Description
Please send your application with the usual informative documents, stating the reference number in the subject line, via the online form. We have compiled further information for you in our FAQ.
In exceptional cases, we will also accept your application documents in paper form addressed to: The President of the University of Kassel, 34109 Kassel, Germany, or via mail to bewerbungen[at]uni-kassel.de, stating the reference number.
In the case of postal applications, please submit only copies of your documents (no folders), as these cannot be returned. All documents will be destroyed after completion of the selection process in compliance with data protection regulations.
The newly established lab at University of Kassel (nablachem.org) is a computational chemistry group investigating:
• How properties of molecules and materials change if you were to locally modify them, e.g. by replacing atoms with those of another element. Treating the system perturbatively in the context of quantum mechanics, allows us to optimize materials to have favourable properties without trying candidate materials one-by-one.
• How to obtain property gradients in computational chemistry from e.g. quantum chemistry methods.
• How to use such gradient information efficiently in machine learning applications.
The specific research projects in this domain will be developed together with the successful applicants.
Tasks:
- How properties of molecules and materials change if you were to locally modify them, e.g. by replacing atoms with those of another element. Treating the system perturbatively in the context of quantum mechanics, allows us to optimize materials to have favourable properties without trying candidate materials one-by-one.
- How to obtain property gradients in computational chemistry from e.g. quantum chemistry methods.
- How to use such gradient information efficiently in machine learning applications.
Requirements:
- Completed course of academic study (Master degree) within the fields of Physics, Chemistry, Materials, or related fields. The degree must have been obtained by the starting date at the latest.
- Enjoy team work and an interdisciplinary environment
- Fluent in English (written and oral)
Advantageous:
- Basic scripting skills (preferably Python)
- Knowledge in machine learning or data analysis or an interest therein
- Experience with scientific computing, preferably atomistic simulations
- Knowledge of German or the willingness to learn it for teaching
The group offers:
- Research in a group with collaborations in the US, Canada, Austria and Spain
- Dedicated budget for training, summer schools, conferences
- Optionally long stays abroad with our collaborators paid for by the group
- Modern office environment and personal notebooks
- Access to large scale compute facilities including cloud computing
- Personalized training in a small group
- Time for personal development
- Optional: part-time work-from-home arrangement
For further information, please contact Prof. Dr. Guido Falk von Rudorff, Tel.: +49 561 804-4762
Our offer:
As an employee of the University of Kassel
- you will be offered an interesting and diverse range of tasks within the framework of a modern and ambitious university,
- you will be part of an interdisciplinary team with a good and collegial working atmosphere,
- you will have the opportunity to participate in professional and interdisciplinary further education measures,
- your workplace is centrally located in the city of Kassel with good public transport connections, which you can currently use for free.
In addition, you will benefit from the advantages of employment in the public service such as:
- an additional company pension (VBL),
- an optional child supplement in accordance with TV-Hessen, a family-friendly university (including childcare for emergencies),
- an annual bonus
- an entitlement to capital-accumulation benefits,
- a promotion of voluntary commitment,
- low-cost participation in university sports and a full range of fitness activities as part of Unifit, as well as workplace health management.
