Assistant Professor of Computer Science (Data Science and Machine Learning) (m/f/d)
23.12.2024
Constructor University Bremen gGmbH
Bremen
Weitere passende Anzeigen:
Passende Jobs zu Ihrer Suche ...
... immer aktuell und kostenlos per E-Mail.
Sie können den Suchauftrag jederzeit abbestellen.
Es gilt unsere Datenschutzerklärung. Sie erhalten passende Angebote per E-Mail. Sie können sich jederzeit wieder kostenlos abmelden.
Assistant Professor of Computer Science (Data Science and Machine Learning) (m/f/d)
Drucken
Bremen
23.12.2024
Constructor University Bremen gGmbH
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.
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.
Assistant Professor of Computer Science (Data Science and Machine Learning) (m/f/d)
Bremen
Aufgaben:
- 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.
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
Wir bieten:
- 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
Unser Kontakt:
For any further information regarding this position, please contact Prof. Alexander Omelchenko, via Mail ( omelchenko@constructor.university ) or job-application@constructor.university .
Weitere Informationen:
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.
Fehlende Berechtigung!
Um Ihnen dieses Stellenangebot anzeigen zu können, müssen Sie essentiellen Cookies zustimmen.
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)
Über uns:
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.
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.
Aufgaben:
- 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.
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
Wir bieten:
- 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
Unser Kontakt:
For any further information regarding this position, please contact Prof. Alexander Omelchenko, via Mail ( omelchenko@constructor.university ) or job-application@constructor.university .
Weitere Informationen:
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.
Berufsfeld
Informationstechnologie, TK
IT/TK Softwareentwicklung
Öffentlicher Dienst, Verwaltung
Consulting, Training, Ausbildung
Bildung, Schulung, Training
Forschung, Lehre
Lehrtätigkeiten
Bundesland
Standorte