Student Assistant (f/m/non-binary) – Support in Empirical Studies and Teaching Activities on Ar[...]

RWTH Aachen; Aachen; Vor Ort; Teilzeit

Zusammenfassung

A prestigious university in Germany seeks a Student Assistant to support research in music data analysis and teaching activities. This part-time position is perfect for those with a passion for music and programming skills in Python. Duties include contributing to research, organizing educational offerings, and assisting with software development. The role offers flexibility and a pay rate of 14.50 € per hour, with a contract term of 12 months which may be extended.

Leistungen

Flexible working hours

Access to university sports and health services

Extensive range of further training courses

Qualifikationen

• Good programming skills in Python are essential.
• Experience in machine learning through courses or practical experience is required.
• An interest in learning additional programming languages is beneficial.
• A passion for music and basic understanding of music theory is preferred.
• Must be enrolled in a university or university of applied sciences.

Aufgaben

• Contribute to research studies on music classification tasks.
• Support organization of educational offerings and design of teaching materials.
• Assist with the development of Advanced Music Explorer (AMUSE).

Kenntnisse

Good programming skills in Python

Experience in machine learning and optimisation

Willingness to learn further programming languages

Passion for music and understanding of music theory

Current studies at a university or university of applied sciences

Tools

PyTorch

Keras

WEKA

scikit-learn

Jobbeschreibung

Student Assistant (f/m/non-binary) – Support in Empirical Studies and Teaching Activities on Artificial Intelligence in Music Data Analysis

Chair of AI Methodology (Computer Science 14)

Our Profile

The Chair for Artificial Intelligence Methodology (AIM), headed by Alexander-von-Humboldt Professor Holger H. Hoos, conducts world-leading research and development of methods in human-centred artificial intelligence (AI) and their broad use for the benefit of society and humanity (“AI for all" and “AI for good"). In addition to research on the technical foundations of AI, particularly on topics in machine learning, automated reasoning and optimisation, our work focuses on AI applications in the fields of medicine and health, climate, music and art.

Music information retrieval or - more widely defined - music data analysis is a highly interdisciplinary research domain with roots in music theory, computer science, signal processing, statistics, psychology, and other sciences. It encompasses computer aided processing and analysis of data sources related to music: audio signals, digital scores, lyrics, album covers, social data, and beyond. Related applications are genre and style recognition, automatic music and accompaniment generation, instrument and vocal detection, music structure analysis, plagiarism detection. To increase quality, efficiency, robustness, and user satisfaction, state-of-the-art AI techniques are applied, such as classification with neural networks, hyperparameter tuning, feature selection, or multiobjective optimisation by means of evolutionary algorithms.

Your Profile

• Good programming skills in Python
• Some experience in machine learning and optimisation (e.g., relevant courses or seminars, experience in PyTorch, Keras, WEKA, scikit-learn)
• Willingness to learn further programming languages (some knowledge in Java and/or Matlab is advantageous)
• Passion for music and basic understanding of music theory (playing a music instrument is not a requirement but is useful)
• Current studies at a university or university of applied sciences

Your Duties and Responsibilities

Depending on current priorities and your experience and personal interests, you will take on tasks from the following areas:

• Contribution to research studies, e.g.:
  • Optimisation of music classification tasks by means of neural architecture search
  • Participation in publications based on study results
• Support in the organisation of educational offerings
  • Tests of new applications, code review
  • Helping with the design of new teaching materials
• Assisting with the development of Advanced Music Explorer (AMUSE), e.g.:
  • Integration of new plugins for feature extraction and classification
  • Enhancement of the user interface and documentation

Please send your application with a short letter of motivation, CV and overview of your academic achievements, preferably by email to the email address below.

What We Offer

The successful candidate will be employed as a student assistant.
The position is to be filled at the earliest possible date and offered for a fixed term of 12 months.
An extension is possible.
This is a part-time contract position.
The standard weekly hours will be 8 hours.
The salary is based on the RWTH Guidelines for Student and Graduate Assistants.
The position corresponds to a pay grade of 14,50 € per hour.

About us

RWTH is a certified family-friendly University. We support our employees in maintaining a good work-life balance with a wide range of health, advising, and prevention services, for example university sports. Employees who are covered by collective bargaining agreements and civil servants have access to an extensive range of further training courses and the opportunity to purchase a job ticket.
RWTH is an equal opportunities employer. We therefore welcome and encourage applications from all suitably qualified candidates, particularly from groups that are underrepresented at the University. All qualified applicants will receive consideration for employment and will not be discriminated against on the basis of national or ethnic origin, sex, sexual orientation, gender identity, religion, disability or age. RWTH is strongly committed to encouraging women in their careers. Female applicants are given preference if they are equally suitable, competent, and professionally qualified, unless a fellow candidate is favored for a specific reason.
As RWTH is committed to equality of opportunity, we ask you not to include a photo in your application.
You can find information on the personal data we collect from applicants in accordance with Articles 13 and 14 of the European Union's General Data Protection Regulation (GDPR) at http://www.rwth-aachen.de/dsgvo-information-bewerbung .

Application

Number

Number V000010450

Application deadline 31/12/2025

Mailing Address

Mailing Address RWTH Aachen University
Chair of AI Methodology (Computer Science 14)
Kim Schrouff
Theaterstr. 35-39
52062 Aachen

Applicants are invited to submit their applications via email. For data protection reasons, however, we recommend sending applications via mail.