Code: 9513.  Our university is one of the research leaders among universities of applied sciences and collaborates with many large companies.

We are looking for by:

Doctoral students (f/m /d)

EG 13 TV-L, Occupancy range 50 % (19.75 h/week)

Reference number 3061 P

Start as early as possible in the context of the BMBF funded application-oriented research project "Transient-Tech" at the Faculty of Chemical and Process Engineering.

Catalytic chemical processes are a key element for the transformation towards a carbon neutral society.

However, the classic development processes for this take a long time. In the project, a technology platform will be established for rapid and data-rich analysis of heterogeneously catalyzed processes. Central to this case is the investigation of non-stationary operating conditions with a rapid online analysis of the gas phase based on ion mobility spectrometry and gas sensors.

Based on these results, the kinetic models will be determined.

The doctorate is awarded via the BW-CAR doctoral center in Baden-Württemberg directly at our University.

There is close interaction in the project with the hte partner company (BASF group).

The regular exchange of ideas at scientific conferences is an integral part of the project.

The tasks are on the one hand the execution of the analysis in collaboration with the development of the process, on the other hand the development of data analysis strategies based on machine and deep learning.

The interface between advanced process analysis and machine learning is one of the most in-demand skills in industry and research.

You will work in state-of-the-art laboratories in a small, application-oriented research team of six PhD students.

The regular exchange of ideas at scientific conferences is an integral part of the project.

The tasks are on the one hand the execution of the analysis in cooperation with the development of the process, on the other hand the development of data analysis strategies based on machine learning and deep learning.

The interface between advanced process analysis and machine learning is one of the most in-demand skills in industry and research.

Main tasks:

Conducting investigations as part of the research project.

This includes, but is not limited to:

Develop data analysis procedures for GC-IMS and other hyphenation techniques.

Development and design of data augmentation techniques for generating synthetic data, for example using neural networks

Development and adaptation of new multivariate evaluation techniques (GAN, ANN) and development of evaluation systems (Matlab, Python)

Development of gas sensor arrays based on Red Pitaya, Raspberry Pi, etc.

Evaluation and comparison with the literature

Presentation of results and drafting of publications

Supervision of students during their theses and dissertations

General laboratory activities

Requirement profile:

Masters/University Diploma in Chemistry, Food Chemistry or similar

Excellent academic performance

experience in analyzing mixtures of complex substances by GC-IMS, GC-MS or comparable

Knowledge of the use of instrument software is required, e.g. Chemstation, LabSolution

Hands-on experience with chemometrics, multivariate statistics and Python programming skills are required, but will also be honed during the assignment

Experience in other languages is also desirable, such as MatLab or R.

In-depth familiarization with the subject will take place in the workplace.

Experience in gas chromatography and hyphenation techniques

Extensive knowledge of organic chemistry

Ability and willingness to learn new subjects

We offer:

Intense scientific exchange

Systematic support for your PhD in small groups

Public service benefits under the TV-L, such as company pension scheme, capital formation benefits and a special annual payment

Travel allowance when using work ticket

Corporate health management measures

Work in a convenient location with excellent VRN and DB connections

Always check the duration of the search with the company.

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