Project work in the BMBF project MALSCO: "Machine Learning for SANS from Colloids".
Task is the investigation of structural changes during colloidal reactions by analysis of scattering data with methods from Machine Learning with the aim of a substantially improved product control. ln this context an existing reactor set-up shall become improved further and be used for the study of different colloid and polymer reactions in which reaction parameters become systematically varied. Central aim is the analyis of the obtained scattering data (primarily small-angle neutron scattering) by methods from Machine Learning for an optimised interpretation of these data. This work will be done at the Institut Laue-Langevin, a world-leading international research institute in Grenoble, France, und at TU Berlin, where the primary place of work can be flexibly decided.

• Successfully completed university degree (Master, Diploma or equivalent) and successfully completed PhD in Scientific Computing, physics chemistry or related subjects
• Comprehensive knowledge of the application of methods from Machine Leaming are required
• A good knowledge of the application of scattering methods for the characterisation of nanostructured systems is wished for, as well as good knowledged from the field of physics and chemistry of colloids and polymers
• Good knowledge of German and/or English required; willingness to acquire the respective missing language skills

Please send your application with the reference number and substantial documents (in a single pdf file, max. 5 MB) by email to Prof. Dr. Gradzielski ( tc7@molmat.tu-berlin.de ).

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To ensure equal opportunities between women and men, applications by women with the required qualifications are explicitly desired. Qualified individuals with disabilities will be favored. The TU Berlin values the diversity of its members and is committed to the goals of equal opportunities. Applications from people of all nationalities and with a migration background are very welcome.