Adjunct Professor
hace 2 días
Madrid
Adjunct Professor of Machine Learning IE University - School of Science & Technology Location: Madrid / Segovia (on-campus, live in-person teaching) Contract: Adjunct / part-time faculty (per-course) Language of instruction: English Start: September 2026 About IE University IE University's School of Science & Technology brings together computer science, artificial intelligence, mathematics and engineering in a teaching model that is collaborative, active and applied. Our students build knowledge by doing, working through real problems in individual and group settings. We are looking for a practitioner-scholar in machine learning who can bring both technical depth and hands-on industry perspective to the classroom. The role We are hiring an adjunct professor to teach three groups across two compulsory third-year courses: One group of AI - Machine Learning & Analytics (6 ECTS, 30 live in-person sessions). Part of the Dual Degree in Business Administration & Data and Business Analytics (BBADBA). Two groups of AI - Reasoning & Problem Solving (6 ECTS, 30 live in-person sessions each). Part of the Bachelor in Computer Science and Artificial Intelligence (BCSAI). Each course carries a teaching load of 30 sessions and a total student workload of 150 hours. All teaching is delivered in English. AI - Machine Learning & Analytics A "from theory to practice" course covering the foundations of modern AI. The syllabus moves from classical machine learning on tabular data (supervised and unsupervised methods, random forests, XGBoost, clustering, recommender systems) through deep learning and computer vision (fully connected and convolutional networks, transfer learning, generative models such as autoencoders, GANs and diffusion) to natural language processing and LLMs (transformers, prompt engineering, API integration, Gradio, LangChain). Fairness and ethics in AI are introduced early. Teaching is hands-on, built around Jupyter notebooks, Python (scikit-learn, TensorFlow/Keras), Kaggle competitions and a group project. AI - Reasoning & Problem Solving An introductory course to the foundations of AI: intelligent agents, problem solving and search (uninformed, informed and local search), search in complex and non-deterministic environments, adversarial search and games (minimax, alpha-beta, Monte Carlo Tree Search, game theory), constraint satisfaction problems, knowledge representation and reasoning (logical agents, first-order logic, planning), reasoning under uncertainty, probabilistic programming, and reasoning in LLMs. Students implement search algorithms, CSP solvers and game-playing agents in Python through individual and group assignments. Responsibilities Deliver live in-person lectures and coding sessions for the three assigned groups, following the established course syllabi. Prepare and run practical assignments, in-class exercises and Jupyter-notebook demonstrations. Set, supervise and grade assignments, quizzes, exams and group projects in line with each course's evaluation criteria. Provide student guidance and hold office hours on request. Uphold IE University's attendance, academic integrity and ethics policies. Requirements PhD (or near completion) in computer science, artificial intelligence, mathematics, statistics, physics or a closely related field. An exceptional professional track record may substitute for the doctorate. Strong command of machine learning, deep learning and classical AI (search, reasoning, agents). Proficient in Python and its ecosystem (scikit-learn, TensorFlow/Keras, pandas, and standard AI/ML libraries). Demonstrated ability to teach technical material to a mixed audience, including business-track students in the analytics course. Full professional fluency in English. Eligibility to work in Spain. Desirable Industry or applied research experience in AI/ML that can be brought into the classroom. Familiarity with current LLM tooling and generative AI workflows (transformers, RAG, prompt engineering, Gradio, LangChain, Hugging Face). Prior university teaching experience, ideally in an active, project-based environment. Experience supervising student projects delivered as working code (e.g. GitHub repositories). What we offer The opportunity to teach at one of Europe's leading innovation-focused universities. A collaborative faculty community at the intersection of technology and business. Flexible, per-course adjunct engagement that fits alongside professional or research commitments. How to apply Please submit a CV, a short statement of teaching interest, and (if available) evidence of teaching effectiveness to the School of Science & Technology. Applications are reviewed on a rolling basis. IE University is committed to diversity and equal opportunity. We welcome applications from all qualified candidates regardless of background.
Avenida de Menéndez Pelayo, Madrid
