Assistant Professors of Computer Science (Data Science and Machine Learning)

Constructor University (formerly Jacobs University) is a private, state-accredited, English-language university in Bremen. We offer Bachelor, Master, and PhD programs in three schools: School of Science, School of Computer Science and Engineering, and School of Business, Social and Decision Sciences. Our principles are first-class teaching and research, international diversity, and transdisciplinary cooperation. According to the 2024 Times Higher Education (THE) World University Rankings, Constructor University is among the top 25 percent out of more than 1900 universities worldwide and is ranked as the second most international university in the world. As an international university, we attract highly talented and open-minded students from all over the world. Currently, over 1,600 students from 110 nations live and study on our residential campus.

The university is currently driving an ambitious expansion of research related to Computer Science, Software Engineering, and Data Science. In this context, a new Assistant Professorship with a focus on Data Science and Machine Learning has been opened in the School of Computer Science and Engineering. Accordingly, Constructor University invites applications from interested candidates for the following position, to be filled ideally by August 2025:

Assistant Professors of Computer Science (Data Science and Machine Learning) (m/f/d)

(full time; 38.5 hrs./week; tenure track)

Your responsibilities:

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.

Your qualifications:

• 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

What you can expect at Constructor University:

Constructor University unequivocally guarantees the academic freedom of every member of the faculty, as well as every other member of the Constructor University community. We encourage diversity in the University in ethnic, cultural, social, religious, political, and national backgrounds, as well as in individual lifestyle. Constructor University offers full equality of opportunity to all qualified applicants and is an equal opportunity employer.

Constructor University consistently achieves top results in national and international university rankings.

In the CHE Ranking, the most comprehensive and detailed ranking of the German-speaking higher education landscape, Constructor University has achieved top placements every year since its first participation in 2005.

• Flexible working hours for work-life balance
• Option for remote work
• Individual onboarding, support, and development planning
• Corporate fitness with EGYM Well Pass (formerly Qualitrain)
• In collaboration with Deutsche Dienstrad – Lease a company bike, whether it's a bicycle, road bike, or e-bike, for both private and business use.
• Green campus with recreational areas and extensive dining options
• Constructor University has comprehensive sustainability and environmental programs

Your application:

For any further information regarding this position, please contact Prof. Alexander Omelchenko, via Mail (omelchenko@constructor.university) or job-application@constructor.university.

Apply today - it's simple and uncomplicated. We look forward to getting to know you. The deadline for applications is January 21st, 2025.

Please upload your documents in a single PDF document, including a letter of motivation stating your field of expertise, curriculum vitae, teaching portfolio and publication record, copies of certificates and diplomas, certification of English proficiency (optional), and the names and addresses of two referees in our application management system. In order to do so, click on the Apply Button and proceed through the individual steps to complete your application.

https://constructoruniversity.wd103.myworkdayjobs.com/en-US/Careers/job/Assistant-Professors-of-Computer-Science--Data-Science-and-Machine-Learning----m-f-d-_JR100158

The offered position is tenure track, with review of performance after a first contract of three and a second contract after another three years. Successful evaluation leads to permanence and typically promotion to associate professor level.

The review of applications will begin immediately. Please note that only applications submitted through the official application portal will be considered for recognition.