Assistant Professor in Computer Science
2 months ago
Kings Cornerstone International College is a dynamic and innovative educational institution committed to providing high-quality education in the fields of Data Analytics, Cybersecurity, and Artificial Intelligence. We are dedicated to preparing students for successful careers in these rapidly evolving and critical domains, and we are seeking a passionate and knowledgeable instructor to join our team.
**Key Responsibilities**:
- Create and update course materials, syllabi, and assessments for courses related to Data Analytics, Cybersecurity, and Artificial Intelligence.
- Deliver engaging and effective lectures, hands-on labs, and workshops to students, ensuring that the content is up-to-date and aligned with industry standards.
- Foster a supportive and interactive learning environment, encouraging student participation and collaboration.
- Provide one-on-one guidance and support to students, helping them develop their skills and knowledge in Data Analytics, Cybersecurity, and Artificial Intelligence.
- Continuously update your knowledge of industry trends, tools, and technologies, and incorporate these updates into your teaching materials.
- Provide constructive feedback to students and work with them to enhance their performance.
**Qualifications**:
- A master's degree in a related field (e.g., Data Science, Cybersecurity, Artificial Intelligence).
- Proven experience in teaching and curriculum development.
- In-depth knowledge of Data Analytics, Cybersecurity, and Artificial Intelligence concepts, tools, and technologies.
- Industry certifications (e.g., CISSP, CompTIA Security+, AWS Certified Machine Learning) are a plus.
- Strong communication and presentation skills.
- A passion for teaching and the ability to inspire students.
- Continuous learner with a commitment to staying current in the field.
Pay: ₹30,000.00 - ₹40,000.00 per month
**Benefits**:
- Provident Fund
Schedule:
- Day shift
**Education**:
- Master's (preferred)
**Experience**:
- Teaching: 1 year (preferred)
- total work: 1 year (preferred)
Work Location: In person
Expected Start Date: 01/06/2024
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