Informationen zur Anzeige:
Assistant Professor of Computer Science (Data Science and Machine Learning) (m/f/d)
Bremen
Aktualität: 23.12.2024
Anzeigeninhalt:
23.12.2024, Constructor University Bremen gGmbH
Bremen
Assistant Professor of Computer Science (Data Science and Machine Learning) (m/f/d)
Aufgaben:
You will support our research and teaching activities in the field of Computer Science by establishing an independent research group focusing on research topics related to Data Science and Machine Learning, including but not limited to deep learning algorithms, predictive analytics, and big data technologies. Possible areas of interest are:
Neural networks and cognitive computing
Data mining and predictive modeling
Statistical learning and optimization
The successful candidate is expected to support teaching in Computer Science at Bachelor and Master level (for example, courses like "Machine Learning," «Deep Learning-, "Statistics and Data Analytics," "Recommender Systems"); as well as develop and implement innovative, pedagogically sound approaches to online, hybrid and in-person teaching and learning; advise students on their studies; and supervise Bachelor, Master-s and PhD theses and research projects.
The university is highly supportive of junior faculty, providing both formal and informal mentoring, administrative support, as well as a flexible budget for establishing an internationally visible research group. Several opportunities exist to develop transdisciplinary research projects in collaboration with other research groups or our industrial partners.
Qualifikationen:
PhD degree in Computer Science or a related discipline
Strong publication record related to Data Science and Machine Learning
Experience and success in teaching in the context of international and diverse environments
Demonstrable interest in innovative teaching and learning approaches
Experience in transferring research knowledge to solving problems in engineering and science
Responsible, self-motivated person able to work independently and as a part of a team
Excellent verbal and written communication skills
Intercultural experience and competence
Fluency in English, the language of instruction and communication on campus
Berufsfeld
Bundesland
Standorte