PhD student (m,f,d)

22.01.2024, Wissenschaftliches Personal

The Leibniz Institute for Food Systems Biology at the Technical University of Munich (Leibniz-LSB@TUM) is a research institution of the Leibniz Association. The working group "Molecular Modeling" at Leibniz-LSB@TUM is looking for a PhD student to start on 01/04/2024

The Leibniz Institute for Food Systems Biology at the Technical University of Munich (Leibniz-LSB@TUM) is a research institution of the Leibniz Association that combines methods of biomolecular basic research with analysis methods of bioinformatics and analytical high-performance technologies to investigate the complex interplay between the human organism and food ingredients.

The working group "Molecular Modeling" at Leibniz-LSB@TUM is looking for a

to start on 01/04/2024

The straightforward identification of chemosensory active molecules in food is largely hampered by the complex food composition, which can lead to masking effects and molecular interactions in the food matrix. The applicant will work on the development of machine learning prediction models for the identification of food-derived taste and odor active compounds.

• Chemoinformatics and machine learning: chemical space analyses, QSAR modeling, machine learning and relevant tools, pharmacophore modeling, molecular docking, virtual screening

The ideal applicant might have various backgrounds. These backgrounds may include but are not limited to: computational chemistry, computer science, applied mathematics, computational biology, bioinformatics, and many other subjects relevant to the project. Excellent communication skills in English, verbally as well as in scientific writing, are required. Above-average interest in the topic, we consider self-motivation and the ability to face new professional challenges as self-evident prerequisites. The ability to work independently, outstanding team skills and organizational aptitude round-out the ideal profile.

• a performance-related salary in accordance with TV-L, in-line with your personal qualifications and the personal prerequisites
• an interesting and varied task area in the field of university research
• a motivated team that is looking forward to welcoming you • scientific development opportunities in an international and interdisciplinary research environment
• training and advanced qualifications within the Leibniz Association and the Technical University of Munich
• flexible working times and therefore good compatibility of work and family
• company pension scheme

In the case of essentially reciprocal suitability, severely-disabled applicants as defined SGB IX will be preferred.

Please address any questions on current topics to [email protected] e and get in touch if you think you would be interested in working as part of our team. Send your application with the usual documents, containing your comprehensive CV and transcripts as well as names of three potential references electronically as a PDF file to the following address,

citing the reference number 2024-03-S3-ADP

to Anja Magalowski (Human Resources Department) [email protected] .

As a part of your application for a position at Leibniz-LSB@TUM, you have submitted personal data to us. Please note Please note our data protection information in accordance with Art. 13 of the General Data Protection Regulation (GDPR) regarding the collection and processing of personal data in the context of your application. By submitting your application, you confirm that you have taken note of the data protection information of Leibniz-LSB@TUM.

The position is suitable for disabled persons. Disabled applicants will be given preference in case of generally equivalent suitability, aptitude and professional performance.

Data Protection Information:
When you apply for a position with the Technical University of Munich (TUM), you are submitting personal information. With regard to personal information, please take note of the Datenschutzhinweise gemäß Art. 13 Datenschutz-Grundverordnung (DSGVO) zur Erhebung und Verarbeitung von personenbezogenen Daten im Rahmen Ihrer Bewerbung. (data protection information on collecting and processing personal data contained in your application in accordance with Art. 13 of the General Data Protection Regulation (GDPR)). By submitting your application, you confirm that you have acknowledged the above data protection information of TUM.

Kontakt: [email protected]