Research Assistant (PhD candidate)
Technische Universität Berlin
Faculty IV - BIFOLD / Machine Learning
Technische Universität Berlin offers an open position:
Research Assistant - salary grade E13 TV-L Berliner Hochschulen - 1st qualification period (PhD candidate)
Part time employment may be possible
The Berlin Institute for the Foundations of Learning and Data (BIFOLD) at TU Berlin (Prof. Klaus Robert Müller) is seeking a Research Associate in Machine Learning. The project will be carried out in the research group "Machine Learning for Molecular Simulation in Quantum Chemistry” (https://www.bifold.berlin/people/dr-stefan-chmiela.html) led by Dr. Stefan Chmiela.
Dr. Chmiela’s team is engaged in the modeling of multi-body systems with applications in quantum chemistry, particularly for predicting solutions to the Schrödinger equation. The overarching goal of the team is the development of models to accelerate accurate molecular dynamics simulations for the calculation of dynamic and thermodynamic observables of physical systems.
Tasks
Independent and responsible research in the field of machine learning. The goal of the advertised project is the development of scalable methods for modeling atomic interactions in quantum chemistry. The focus is on dimension reduction of partial differential equations to describe essential properties of electronic systems at the atomic level.
The associated tasks are:
Development and implementation of ML models in quantum chemistry; Incorporation of physical knowledge about the target systems into the models, e.g., distinguishing different kinds of short- and long-range interactions between atoms; Evaluation of the developed methods using benchmark problems and contextualizing observations within physical theory; Communication of results through presentations. teaching tasks
Requirements
Successfully completed university degree (Diploma, Master, or equivalent) in Physics, Mathematics, or Computer Science Proven experience in machine learning with a strong understanding of algorithms, linear algebra, functional analysis, and related mathematical concepts Solid knowledge in physics, including methods for solving the Schrödinger equation Excellent programming skills in Python and solid knowledge of common machine learning frameworks such as PyTorch or TensorFlow Strong communication skills in English and the ability to explain complex topics to a broad audience with diverse backgrounds (i.e., both computer scientists and physicists) Familiarity with state-of-the-art machine learning models and approaches for modeling molecular force fields with ML The ability to teach in German and/or in English is required; willingness to acquire the respective missing language skills
Desirable.
The ability to interact with a team of ML experts and physicists.
How to apply
Please send your written application, quoting the reference number, with the usual application documents (i.e. at least cover letter, CV, graduation certificates, grade overviews, etc.) to Technische Universität Berlin - Die Präsidentin - Fakultät IV, Institut für Softwaretechnik und Theoretische Informatik, FG Maschinelles Lernen, Prof. Dr. Müller, MAR 4-1, Marchstr. 23, 10587 Berlin or by e-mail (one PDF file, max. 5 MB) to: ****@b*****d.berlin.
For cost reasons, application documents sent by mail will not be returned. Please submit copies only.
By submitting your application via email you consent to having your data electronically processed and saved. Please note that we do not provide a guarantee for the protection of your personal data when submitted as unprotected file. Please find our data protection notice acc. DSGVO (General Data Protection Regulation) at the TU staff department homepage: https://www.abt2-t.tu-berlin.de/menue/themen_a_z/datenschutzerklaerung/ or quick access 214041.
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. pplications from people of all nationalities and with a migration background are very welcome.
Download PDF Facts Published 19.11.2024 Number of employees ca. 7000 Category Graduate position, Research assistant, PhD position Location Germany, Berlin, Berlin, Charlottenburg Area of responsibility Computer science Start date (earliest) Earliest possible Duration for 5 years Full/Part-time full-time; part-time employment may be possible Remuneration Salary grade E13 Homepage http://www.tu-berlin.de Requirements Qualification Master, Diplom or equivalent Field of study Engineering, Computer science, Mathematics, Physics Apply Application deadline 31.12.2024 Reference number IV-382/24 By post
Technische Universität Berlin
- Die Präsidentin - Fakultät IV, Institut für Softwaretechnik und Theoretische Informatik, FG Maschinelles Lernen, Prof. Dr. Müller, MAR 4-1, Marchstr. 23, 10587 Berlin
By email ****@b*****d.berlin
Verweise auf baito
Du findest gut, was wir machen? Du kannst uns dabei unterstützen. Gib bei deiner Bewerbung an, dass du die Stelle bei baito gefunden hast.