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This position serves the purposes of the vocational and scientific education of graduates of diploma or master’s degree programmes and sets the goal of completing a corresponding doctoral degree according to the allocation of the position to either the Department of Economics or the Department of Networked and Embedded Systems. Applications by individuals who have already completed a subject-specific doctoral degree or a subject-relevant PhD programme therefore cannot be considered.
The position is funded through the university’s Ada Lovelace Programme, which aims at fostering interdisciplinary research at the university. The successful candidate will therefore be jointly supervised by two academic professors, one from the field of computer engineering and one from the field of economics, and will be affiliated with one of the two departments.
The successful candidate will work within the project “A Machine Learning Approach to Smart Electricity Load Management: From Disaggregation to Policy Impact Evaluation”. This project covers both technical aspects (development/implementation of statistical and machine learning methods, algorithm design and implementation) as well as economic impact analysis (using i.a. modern micro-econometric techniques). Further information on the research project is available upon request.
Prerequisites for the position:
- Diploma or master’s degree in computer science, data science, economics, electrical engineering, information systems, information technology, mathematics, statistics or related fields (with a strong formal background) at a higher education institution
- Good academic record
- Interest in developing and applying algorithms for analysing large and complex data sets, interest in big data-based econometric impact and evaluation research
- Experience in scientific programming (e.g., Python or R)
- Fluency in English (written and spoken)
Desired qualifications:
- Experience in at least one of the following areas: Econometrics, Machine Learning, Non-Intrusive Load Monitoring, Time Series Analysis (e.g., large numbers of high-frequency time series of individual household electricity consumption data)
- Social and communication competences, interest in and ability to work in teams
- Strong motivation and output orientation
- Ability to work independently in scientific projects with a focus on high quality and precision
- Scientific dissemination skills, e.g., via scientific publication(s)
If you are interested in this position, please apply in English providing the following documents:
- Letter of application
- Curriculum vitae (with detailed information on your degrees including date/place/grade, the experience acquired, the thesis title, the list of publications if any, and any other relevant information)
- Copy of the degree certificates and transcripts of the courses
- Any certificates that can prove the fulfilment of the required and additional qualifications listed above (e.g., the submission of the final thesis/dissertation if required by the degree programme, copy of publications, programming skills certificates, language skills certificates, list of further
- dissemination activities etc.)
- In case a diploma or master’s degree certificate cannot be included in the application package, provide a written declaration of the supervisor on the expected date of completion of the study programme. Note that we plan to fill the position as soon as possible.
- A conferred title (diploma / master’s degree) is a necessary condition for employment. Proof has to be provided two weeks prior to appointment at the latest.
To apply, please select the position with the reference code 349/24 in the category “Scientific Staff”
using the link “Apply for this position” in the job portal at http://jobs.aau.at/en/.