Job opportunities

At SCC you work in an innovative organisation with an excellent reputation; an organisation in the middle of international technological developments that helps accellerating science. If you wish to set ambitious goals, find freedom and flexibility in your work and continue to develop your personal strengths, then a job at SCC is just the thing for you. We are always happy to receive your application, even if currently no vacancies are listed, a job opening for researchers, administrators, scientific supporters is always around the corner.

Are you interested in working with us? Then send your speculative application to: personal∂scc.kit.edu

Students interested in working as a research assistant or looking for a topic for their master or bachelor thesis are also welcome. Theses can be supervised primarily in computer science or mathematics, but we also have good contacts to other KIT faculties.

SCC

The Scientific Computing Center (SCC) is the Information Technology Centre of KIT. We work in a wide variety of projects with universities, research institutions and companies, both nationally and internationally. Topics range from the analysis of large scale data to data-intensive computing and cloud computing to parallel and numerical methods. We develop and operate innovative IT services as well as large research facilities.

Overview

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Jobs at SCC

PhD position Untangling multi-property NMR signals in drug screening with data-driven neural networks
75% part-time

Category

Job description

Within the Collaborative Research Center (SFB) HyPERiON at KIT, an innovative PhD project is offered that focuses on resolving signal overlap in parallel NMR spectroscopy using artificial intelligence (AI). NMR spectroscopy is a key tool in drug discovery. However, in a parallel setup, signal couplings and overlaps occur that make it difficult to extract critical molecular information. The aim of the project is to develop AI models capable of generating individual, decoupled spectra from coupled NMR spectra.

Within the scope of the project, your responsibilities will include:

  • Developing a transformer-based neural network for the processing of NMR spectra
  • Creating datasets from existing experiments within the CRC and from your own experiments, which are to be carried out during a research stay at KIT’s Institute of Microstructure Technology (IMT)
  • Applying self-supervised pretraining based on masked sequence modeling and task-specific fine-tuning to the trained neural network
  • Analyzing the extent to which the developed model can learn the underlying physical principles of nuclear magnetic resonance

You will further be part of HyPERiON, participating in CRC activities and engage with the other PhD students and projects.

Key Focus Areas

  • Scalable deep learning methods for nuclear magnetic resonance
  • Self-supervised pre-training techniques and transfer learning approaches in Transformer-based architectures
  • GPU-based computing and high-performance computing (HPC)
  • Application of AI methods in a scientific context

Personal qualification

Job requirements:

  • M.Sc. in computer science, physics, mathematics or equivalent discipline
  • Very good programming and software development skills, preferably in Python
  • Prior experience with deep learning model development and training, or nuclear magnetic resonance methods

 

More details Apply

Offers for students

Doctoral theses, final theses, master's theses and bachelor's theses

  1. The Data Analytics, Access and Applications (D3A) department offers master's and bachelor's theses
  2. The Data Exploitation Methods (DEM) department offers graduate and doctoral theses
  3. The research group Methods for Big Data(MBD) offers master theses
  4. The Scientific Computing & Mathematics(SCM) department offers master's and bachelor's theses
  5. The Uncertainty Quantification (UQ) research group offers master's and bachelor's theses

Mentoring program for female STEM students

The new mentoring program Warp4IT "Women as research peers for Information Technology" aims to give female STEM students an insight into the working life of female scientists through project work.
female scientists through project work. Further information: Women's Network

Student assistants wanted

  1. Offers in the department Data Analytics, Access and Applications(D3A)
  2. Offers of the research group Methods for Big Data (MBD)
  3. Offers in the department Networks and Telecommunications
  4. Offers in the department Scientific Computing & Simulation