p Adjunct Professor of Machine Learning /pbrSi está considerando enviar una solicitud, asegúrese de pulsar el botón de solicitar de abajo después de leer la descripción completa.brpb IE University - School of Science Technology /b /ppstrong Location: /strong Madrid / Segovia (on-campus, live in-person teaching) /ppstrong Contract: /strong Adjunct / part-time faculty (per-course) /ppstrong Language of instruction: /strong English /ppstrong Start: /strong September 2026 /ppb About IE University /b /pp 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. /ppb The role /b /pp We are hiring an adjunct professor to teach three groups across two compulsory third-year courses: /pullib One group of AI - Machine Learning Analytics /b (6 ECTS, 30 live in-person sessions). Part of the Dual Degree in Business Administration Data and Business Analytics (BBADBA). /lilib Two groups of AI - Reasoning Problem Solving /b (6 ECTS, 30 live in-person sessions each). Part of the Bachelor in Computer Science and Artificial Intelligence (BCSAI). /li /ulp Each course carries a teaching load of 30 sessions and a total student workload of 150 hours. All teaching is delivered in English. /ppb AI - Machine Learning Analytics /b /pp 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. /ppb AI - Reasoning Problem Solving /b /pp 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. /ppb Responsibilities /b /pulli Deliver live in-person lectures and coding sessions for the three assigned groups, following the established course syllabi. /lili Prepare and run practical assignments, in-class exercises and Jupyter-notebook demonstrations. /lili Set, supervise and grade assignments, quizzes, exams and group projects in line with each course's evaluation criteria. /lili Provide student guidance and hold office hours on request. /lili Uphold IE University's attendance, academic integrity and ethics policies.



/li /ulpb Requirements /b /pulli 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. /lili Strong command of machine learning, deep learning and classical AI (search, reasoning, agents). /lili Proficient in Python and its ecosystem (scikit-learn, TensorFlow/Keras, pandas, and standard AI/ML libraries). /lili Demonstrated ability to teach technical material to a mixed audience, including business-track students in the analytics course. /lili Full professional fluency in English. /lili Eligibility to work in Spain. /li /ulpb Desirable /b /pulli Industry or applied research experience in AI/ML that can be brought into the classroom. /lili Familiarity with current LLM tooling and generative AI workflows (transformers, RAG, prompt engineering, Gradio, LangChain, Hugging Face). /lili Prior university teaching experience, ideally in an active, project-based environment. /lili Experience supervising student projects delivered as working code (e.g. GitHub repositories). /li /ulpb What we offer /b /pulli The opportunity to teach at one of Europe's leading innovation-focused universities. /lili A collaborative faculty community at the intersection of technology and business. /lili Versátil, per-course adjunct engagement that fits alongside professional or research commitments. /li /ulpb How to apply /b /pp 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. /pp IE University is committed to diversity and equal opportunity. We welcome applications from all qualified candidates regardless of background. xsgfvud /pbrHay opciones de teletrabajo/trabajo desde casa disponibles para este puesto.

📌 Adjunct Professor (Alcobendas)
🏢 Ie School Of Science And Technology
📍 Alcobendas