Tenure-Track Faculty Positions In Data Science: Machine Learning

Tenure-track Faculty positions in Data Science: Machine LearningJob Title: Assistant Professor in Data ScienceLocation: IE University (Madrid, Segovia)Department: School of Science and TechnologyStart Date: September 2025Position Overview:IE University's School of Science and Technology is seeking a highly qualified candidate for a full-time faculty position in Data Science with a specialization in Applied Machine Learning. We look for candidates with deep expertise in at least one of the following: natural language processing, computer vision, reinforcement learning, generative AI, graph learning, and time series modeling. In addition to technical expertise in the core technologies, the Committee will value positively the candidate's interest in ethical aspects of machine learning, the explainability of AI systems, and the development of privacy-preserving techniques such as federated learning. This role will require the candidate to combine cutting-edge machine learning methods with practical, impactful applications across multiple industries.We value candidates with the capacity to collaborate in applied research projects led by the Impact Xcelerator at IE School of Science and Technology, specifically in one of the three focus areas: Climate/Energy, Healthcare, or Financial Systems. The ability to contribute to multidisciplinary research initiatives that apply cutting-edge technologies to real-world challenges in these sectors will be key to the role's success, providing opportunities to work closely with industry partners and stakeholders to drive innovative solutions.Key Responsibilities:Develop and teach undergraduate and graduate courses on Applied Machine Learning, including core topics such as NLP, Computer Vision, Reinforcement Learning, and Deep Learning.Lead research initiatives that apply machine learning to real-world problems in industries like finance, energy, industry, and healthcare, focusing on areas such as predictive analytics, automation, and AI-driven decision-making, while actively securing competitive research funds.Contribute to research in emerging topics like explainable AI (XAI), ethical considerations in AI, federated learning, model interpretability, and privacy-preserving machine learning.Collaborate with interdisciplinary teams across IE University and industry partners to design and implement machine learning solutions that address complex, domain-specific challenges related to the Impact Xcelerator Labs.Supervise and mentor undergraduate, graduate, and Ph.D. students, guiding them through research projects involving machine learning applications.Design and contribute to innovative curricula, incorporating hands-on learning and real-world case studies.Engage in academic service and play a role in the strategic development of the School of Science and Technology.Required Qualifications:A Ph.D. in Data Science, Computer Science, Engineering, Mathematics or a closely related field.Demonstrated expertise in key areas of Applied Machine Learning, including NLP, Computer Vision, Reinforcement Learning and Deep Learning.A proven research track record with publications in top-tier Machine Learning conferences and journals.Proficiency with modern machine learning frameworks and libraries in Python.Experience designing and delivering high-quality courses in machine learning, with an emphasis on practical applications across industries.Preferred Qualifications:Experience with explainability of machine learning models (XAI) and addressing ethical and societal impacts of AI.Research in federated learning or other privacy-preserving techniques that address concerns related to data security and model privacy.Experience applying machine learning solutions to interdisciplinary fields, particularly business analytics, financial technology, healthcare diagnostics, or industrial automation.Knowledge of emerging fields such as multimodal learning, few-shot learning, adversarial robustness, or generative models.Proven ability to secure research funding and lead collaborative projects across academic and industrial partners.We offer:A competitive salary in line with top-ranked European academic institutions.A generous seed research fund to cover travel, equipment and relocation costs.State-of-the-art campus facilities and support to build your lab infrastructure.A professional and stimulating international working environment with English as the de facto language.Full access to public health services through membership of the National Insurance Scheme plus a discount plan to acquire an additional private health insurance plan.Diversity in an open-minded, inclusive and family-friendly environment.Inspiring campus life on a conveniently located, state-of-the-art unique campus in the hearts of Madrid and Segovia.Application Instructions:Please include a cover letter and a curriculum vitae, a research statement, a statement of teaching philosophy and one confidential recommendation letter. You may include teaching evaluations and sample course syllabi in your dossier.Pre-submission inquiries about the open positions may be addressed to Prof. Dae-Jin Lee (******). For general inquiries, contact Sara Flores (******), Associate Director of Faculty Affairs.We will start screening after December 15. Applications received until this date will be considered for the first round of interviews. The position will remain open until it is filled.About IE University and the School of Science and Technology:IE University is an internationally recognized institution originally founded as a business school. We consider ourselves the most international institution of higher education with approximately 85% of our students coming from outside Spain and typically over 120 countries represented on campus. Our Madrid postgraduate campus is situated in the financial district of this vibrant, cosmopolitan capital city of over 5 million people. In 2021 we opened the IE Tower, standing as one of the 5 towers in the business district of Madrid with a 6000-student capacity.The School of Science and Technology prepares students with industry relevant skills in the context of STEM and related educational programs. The school offers undergraduate and graduate degrees in Computer Science, Artificial Intelligence, Applied Mathematics and Data analytics. For further information on the current faculty and lines of research, please visit IE Research Datalab (https://www.ie.edu/ieresearchdatalab/).
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