pAdjunct Professor of Machine Learning /ppstrongIE University
Si cree que es el candidato ideal para la siguiente posibilidad, envíe su solicitud después de leer la descripción completa.
- School of Science Technology /strong /ppstrongLocation: /strong Madrid / Segovia (on-campus, live in-person teaching) /ppstrongContract: /strong Adjunct / part-time faculty (per-course) /ppstrongLanguage of instruction: /strong English /ppstrongStart: /strong September 2026 /ppbr/ppstrongAbout IE University /strong /ppIE 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.
/ppbr/ppstrongThe role /strong /ppWe are hiring an adjunct professor to teach three groups across two compulsory third-year courses: /pullistrongOne group of AI
- Machine Learning Analytics /strong (6 ECTS, 30 live in-person sessions).
Part of the Dual Degree in Business Administration Data and Business Analytics (BBADBA).
/lilistrongTwo groups of AI
- Reasoning Problem Solving /strong (6 ECTS, 30 live in-person sessions each).
Part of the Bachelor in Computer Science and Artificial Intelligence (BCSAI).
/li /ulpEach course carries a teaching load of 30 sessions and a total student workload of 150 hours.
All teaching is delivered in English.
/ppbr/ppstrongAI
- Machine Learning Analytics /strong /ppA "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.
/ppbr/ppstrongAI
- Reasoning Problem Solving /strong /ppAn 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.
/ppbr/ppstrongResponsibilities /strong /pulliDeliver live in-person lectures and coding sessions for the three assigned groups, following the established course syllabi.
/liliPrepare and run practical assignments, in-class exercises and Jupyter-notebook demonstrations.
/liliSet, supervise and grade assignments, quizzes, exams and group projects in line with each course's evaluation criteria.
/liliProvide student guidance and hold office hours on request.
/liliUphold IE University's attendance, academic integrity and ethics policies.




/li /ulpbr/ppstrongRequirements /strong /pulliPhD (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.
/liliStrong command of machine learning, deep learning and classical AI (search, reasoning, agents).
/liliProficient in Python and its ecosystem (scikit-learn, TensorFlow/Keras, pandas, and standard AI/ML libraries).
/liliDemonstrated ability to teach technical material to a mixed audience, including business-track students in the analytics course.
/liliFull professional fluency in English.
/liliEligibility to work in Spain.
/li /ulpbr/ppstrongDesirable /strong /pulliIndustry or applied research experience in AI/ML that can be brought into the classroom.
/liliFamiliarity with current LLM tooling and generative AI workflows (transformers, RAG, prompt engineering, Gradio, LangChain, Hugging Face).
/liliPrior university teaching experience, ideally in an active, project-based environment.
/liliExperience supervising student projects delivered as working code (e.g.
GitHub repositories).
/li /ulpbr/ppstrongWhat we offer /strong /pulliThe opportunity to teach at one of Europe's leading innovation-focused universities.
/liliA collaborative faculty community at the intersection of technology and business.
/liliFlexible, per-course adjunct engagement that fits alongside professional or research commitments.
/li /ulpbr/ppstrongHow to apply /strong /ppPlease 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.
/ppbr/ppemIE University is committed to diversity and equal opportunity. xqbhyrx
We welcome applications from all qualified candidates regardless of background.
/em /p

📌 Adjunct Professor (Madrid)
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📍 Madrid