Join our College team! We are the largest innovation hub in Europe, but we are also a College. We are looking to expand our brilliant teaching team and we want you to discover how lovely it can be to work in a place that values and promotes:

• Your experience.
• An innovative approach to learning.
• Joy. Our teachers are professional and internationally-minded, but we are all committed to having fun at work.

As part of our BSc (Hons) AI & Data Science program, we are seeking a Professor in Databases to teach and guide students in foundational and advanced database concepts.
As part of our BSc (Hons) AI & Data Science program, we are seeking a Professor in Multivariable Calculus to teach and guide students in foundational and advanced database concepts.

QUALIFICATIONS & EXPERIENCE

• B2 or C1 English Language
• A Master’s or Ph.D. in Mathematics, Applied Mathematics, Computer Science, or a related field.
• Strong expertise in calculus, optimization techniques, and their applications in computer science.
• Experience in teaching at the university level (preferred).
• Industry experience in AI, data science, machine learning, or operations research is a plus.
• Excellent analytical, problem-solving, and communication skills
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The successful candidate will be responsible for delivering the Multivariable Calculus & Optimization course, covering both theoretical concepts and practical applications.

Key duties include:

• Delivering engaging lectures and hands-on workshops on:
• Introduction to Optimization: Definitions, types of optimization problems, and real-world applications.
• Gradient Descent: Using gradients to find function minima/maxima and understanding learning rates.
• Newton’s Method: Utilizing the Hessian matrix for optimization and comparing it with gradient descent.
• Constrained Optimization: Solving problems with constraints using Lagrange multipliers and other methods.
• Convex Optimization: Understanding convexity and exploring convex optimization algorithms.
• Applications in Computer Science: Optimization in network flows, shortest path problems, and machine learning.
• Integrating real-world examples and case studies relevant to AI, data science, and engineering.
• Supervising student coursework, including problem-solving assignments and applied optimization projects.
• Encouraging critical thinking and problem-solving in mathematical modeling.
• Collaborating with faculty to ensure alignment with AI, data science, and technology programs.