FAQs
What is the job title for this position?
The job title is Werkstudentin / Werkstudent Data / Research Scientist (w/m/d).
What academic background is required for this role?
Candidates should be students (Bachelor/Master) in fields such as Machine Learning, Artificial Intelligence, Operations Research, Applied Statistics, Computer Science, Mathematics, Physics, Business Informatics, or comparable study programs.
What programming languages should candidates be familiar with?
Candidates should have experience in transferring mathematical concepts into software components using programming languages, particularly Python.
What type of experience is desirable for this position?
Experience with libraries such as Scikit-Learn, Pytorch, Tensorflow, Gurobi, and ML-Flow is desirable, along with knowledge in operationalizing decision-making machines in an ML-Ops context.
Are there specific documents that need to be submitted with the application?
Yes, candidates must submit a resume, current enrollment certificate, latest transcript of grades, and a certification from the university for mandatory internships. Non-EU applicants also need to provide a work permit.
Who can I contact for more information regarding this job listing?
You can contact Hartmut Fromm for more information about this job listing.
What skills are essential for successful candidates?
Candidates should demonstrate a high degree of initiative, teamwork capability, and strong communication skills.
What tasks will be part of this role?
Tasks include identifying planning decisions that can be addressed by machine learning, transferring optimization approaches to specific use cases, modeling new constraints, implementing scalable software components, and providing proactive feedback for process improvement.
Is this role an internship or a full-time position?
This role is a Werkstudent position, which typically indicates a part-time internship format for students.
What is the focus area of this internship?
The focus is on applying concepts from machine learning, artificial intelligence, and operations research to improve production and logistics in complex supply chain environments.