External Lecturer – Artificial Neural Networks and Deep Learning – DIS Copenhagen

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profile Job Location:

Copenhagen - Denmark

profile Monthly Salary: Not Disclosed
Posted on: Yesterday
Vacancies: 1 Vacancy

Job Summary

DIS Copenhagen is currently hiring part-time faculty to teach or co-teach the course Artificial Neural Networks and Deep Learning starting in January 2026.

Preparation of course content can start in fall 2025. The course is offered twice per year: fall term (mid-August to mid-December) and spring term (mid-January to mid-May). The course includes lectures discussions student-centered learning activities field studies in the Copenhagen region one faculty-led study tour within Denmark one faculty-led study tour to London student assessment grading and feedback.

Pedagogical support training and mentorship are available at DIS through the Learning Lab and experienced faculty. Faculty collaborate with academic support staff in various professional development opportunities.

About the course

Artificial Neural Networks are programs that write themselves when given an objective some training data and abundant computing power. Recently these programs have brought about a wide array of impressive innovations such as self-driving cars face recognition and human-like speech generators. This course offers students an introduction to Deep Artificial Neural Networks (i.e. Deep Learning). With focus on both theory and practice we cover models for various applications how they are trained and tested and how they can be deployed in real-world applications.

View the course syllabus here.

There are many good reasons to teach at DIS including excellent opportunities to:

  • Work in an international informal and enthusiastic academic environment with an emphasis on cross-cultural understanding teamwork innovation collegiality and adaptability
  • Develop interactive experiential teaching skills and teaching experience in English
  • Enhance the cultural competencies of U.S.-based students and emerging professionals by sharing your knowledge of Scandinavia and local best practices
  • Expand professional networks throughout Denmark Europe and the United States

Main tasks and responsibilities

  • Revise and finalize course syllabi in collaboration with DIS staff. Please note: This is an introductory course to various topics within Artificial Neural Networks and Deep Learning taught to computer science students in their third or fourth year of university studies.
  • Teach at DIS Copenhagen. Teaching format includes classroom lectures discussions active learning activities experiential learning activities and field studies.
  • Plan academic visits and travel with students in faculty-led study tours
  • Assess students performance grade assignments and provide feedback to students throughout the course
  • Participate in meetings/workshops to develop pedagogical skills in line with the DIS teaching philosophy
  • Participate in and support curriculum development process
  • Develop material for new courses

Professional competencies

  • Relevant background (preferably PhD in computer science or related field) professional computer science experience and hands-on expertise within the field of the course
  • Proficiency in English language
  • Interest in instructing undergraduate-level students from North American institutions
  • Open to pedagogical support from DIS and capable of incorporating DIS interactive and hands-on teaching philosophy into teaching practice
  • Experience creating a structured and interactive learning environment is an advantage

Application process

Please submit your CV and application letter addressing the professional competencies above in English. Applications will be processed as received.

Contact information

For additional information please send an e-mail to


Required Experience:

Intern

DIS Copenhagen is currently hiring part-time faculty to teach or co-teach the course Artificial Neural Networks and Deep Learning starting in January 2026.Preparation of course content can start in fall 2025. The course is offered twice per year: fall term (mid-August to mid-December) and spring ter...
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