Student Assistant (f/m/non-binary) Support in Teaching Activities and Empirical Studies for Optimisation of Music Data Analysis using Artificial Intelligence

Weitere Informationen

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 initially 6 months.
Desired is a long-term commitment, so applications from students in their BSc studies are welcome.
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 13,25 € per hour.

Unser Profil

The Chair for Artificial Intelligence Methodology (Informatik 14), 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, art and music.

Music Information Retrieval or – more generally defined – Music Data Analysis is a highly interdisciplinary research domain which involves computer aided processing and analysis of data sources related to music: audio signals, digital scores, lyrics, album covers, etc. Related applications include genre and style recognition, automatic music and accompaniment generation, instrument and vocal detection, music structure analysis, plagiarism detection. To increase the quality and the efficiency, many techniques can be applied, such as automatic hyperparameter tuning, classification with neural networks, feature selection, or multi-objective optimisation by means of evolutionary algorithms. The scope of this student position is to provide support for studies optimising various music data analysis applications, and also to integrate them into educational offerings at the chair of Artificial Intelligence Methodology, amongst others enhancing the open source Java framework AMUSE (Advanced MUSic Explorer).

Additional information can be found on our website: https://www.aim.rwth-aachen.de.

Ihr Profil

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

Ihre Aufgaben

• Implementation of AMUSE extensions (integration of new plugins for feature extraction and classification, enhancement of the user interface, documentation)
• Contribution to research studies (e.g., comparison of algorithms for prediction of instruments, harmonies, or emotions, optimisation by means of neural architecture search), as well as publications based on study results
• Support in the organisation of educational offerings (test of new applications, review of code, participation with own ideas)
• Support in the implementation of demos / participation in school projects, e.g., for InfoSphere – Student Laboratory for Computer Science

Please send your application with a brief letter of motivation, CV, and an academic transcript preferably by email to the email address mentioned below.

Über uns

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.

Besoldung / Entgelt

13,25 € per hour