Professor of Computer Science

2 days ago

Doha, Baladīyat ad Dawḩah, Qatar Carnegie Mellon University Full time
Roles and responsibilities

Responsibilities include supporting two to three advanced undergraduate courses per year, holding recitations/office hours, working closely with students, and supporting our general educational mission. In addition to this load, successful candidates are expected to conduct research in collaboration with CMU-Q faculty or local partners.

We are particularly interested in candidates in the areas of Theoretical Computer Science, Artificial Intelligence, Machine Learning, or Deep Learning. Outstanding candidates in other areas are also encouraged to apply. CMU Qatar's benefits package is highly attractive, with salaries comparable to those in the US, but free of tax. Relocation, housing, transportation, and health benefits are also covered.
Teaching and Instruction

Deliver lectures, tutorials, and practical sessions on various computer science topics, including algorithms, data structures, software engineering, artificial intelligence, machine learning, databases, and computer networks.
Develop and update course materials, including syllabi, lectures, assignments, quizzes, and exams, ensuring they reflect current trends and technological advancements in computer science.
Foster an engaging and interactive learning environment by incorporating real-world applications, case studies, and hands-on projects.
Curriculum Development

Design and implement new courses or update existing ones based on the latest research, technological developments, and industry needs.
Ensure the curriculum covers foundational computer science principles as well as specialized areas like cloud computing, cybersecurity, data science, and mobile computing.
Collaborate with other faculty members to ensure a coherent and interdisciplinary approach to computer science education.
Research and Scholarly Activities

Conduct original research in computer science and publish findings in top-tier journals and conferences in areas such as algorithms, artificial intelligence, machine learning, data science, cybersecurity, or software engineering.
Lead and participate in cutting-edge research projects, seeking funding through grants and collaborations with industry or government organizations.
Stay current with advancements in the field of computer science, exploring new topics and applying emerging technologies in research.
Supervision and Mentorship

Supervise graduate and PhD students in their research, providing guidance on project development, academic writing, and career development.
Encourage students to participate in academic conferences, workshops, and internships to broaden their professional horizons.
Mentor students on technical and professional aspects of computer science, including research methodologies, coding practices, and ethical considerations.

Desired candidate profile

Have completed a PhD in computer science or related fields by the time of being hired.
A proven track record of productive research.
Exceptionally strong communication and interpersonal skills.
Desire to gain hands-on teaching experience.
Be able to work independently, as well as in a team.
A proven track record of teaching computer science subjects at the undergraduate and graduate levels.
Extensive research experience with publications in reputable journals and conferences in computer science.
Experience in supervising PhD, master's, and undergraduate students' research projects or theses.
Research Expertise

Expertise in core areas of computer science such as algorithms, artificial intelligence, machine learning, data science, computer vision, networking, or software engineering.
A strong publication record with contributions to high-impact journals and top-tier conferences.
Experience in conducting interdisciplinary research and collaborating with external research institutions or industry partners.
Teaching and Pedagogical Skills

Strong ability to design and deliver course content, incorporating diverse teaching methods, including lectures, practical labs, and online learning platforms.
Ability to teach a broad range of computer science topics and adapt to evolving technologies.
Familiarity with modern educational tools, including coding platforms, virtual labs, and learning management systems (LMS).

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