Ofertes d'ocupació per a Análisis del comportamiento

• Nivell d'experiència---
• Tipus de contracteA temps complert
• Publicada18 d’oct.

Inglés Coordinación de proyectos Cooperación Composición musical Ciencias de la computación Análisis del comportamiento Sistemas escolares Opiniones de equidad Ciencia cognitiva Calidad de Decisión Machine Learning

About ELLIS Alicante

The ELLIS unit Alicante Foundation (ELLIS Alicante) is a non-profit research foundation based in Alicante, Spain, dedicated to advancing human-centric Artificial Intelligence (AI). Its mission is to develop AI systems that respect human values, support human well-being, and contribute positively to society.

ELLIS Alicante is part of ELLIS (the European Laboratory for Learning and Intelligent Systems), a European network of scientific excellence in machine learning and related fields. ELLIS Alicante is the only ELLIS unit within the 49 units in the network devoted to human-centric AI for Social Good. Hence, it aims to become a European reference in research on ethical and responsible AI for social good.

At ELLIS Alicante, we pursue scientific excellence while investigating how AI can be designed to serve human needs and societal interests. We foster an international, collaborative research environment that encourages intellectual independence, interdisciplinary exchange, and ambitious research with the potential for scientific and societal impact.

About the position

ELLIS Alicante invites applications for a two-year postdoctoral position in Human–AI Teaming and Agentic AI, focusing on how AI agents can collaborate effectively with humans in increasingly complex, multi-agent environments.

As AI systems evolve from individual assistants into teams of interacting agents, a central challenge is understanding how humans can work effectively with these systems, maintain appropriate levels of trust and control, and make informed decisions without becoming overwhelmed by information and interaction demands.

The successful candidate will contribute to research on human-centered methods for adaptive collaboration between humans and AI agents. A central component of the position will be the empirical investigation and evaluation of human–AI collaboration through controlled experiments and, where appropriate, longitudinal studies involving human participants. The research will examine how individual differences, team composition, agent capabilities, and interaction patterns influence collaboration, decision quality, and human experience. The research agenda will also consider how principles of trustworthy and socially aware AI, including fairness, transparency, and norm-sensitive behavior, can support effective human–AI collaboration.

The position will be supported primarily by a Horizon Europe research project, alongside other research funding.

This position offers the opportunity to contribute to an emerging research area at the intersection of agentic AI, human–AI interaction, and empirical evaluation; develop original research ideas; publish at leading international venues; and collaborate with researchers across ELLIS and the wider international research community.

Key responsibilities

· Human–AI teaming and evaluation: Investigate and develop adaptive methods for effective collaboration between humans and AI agents in multi-agent environments, tailoring communication, explanations, task allocation, and autonomy to human needs, capabilities, and preferences. Investigate cognitive load, trust, fairness, and human oversight, and evaluate the proposed methods through controlled experiments and, where appropriate, longitudinal human-subject studies, assessing collaboration quality, decision-making, usability, and human-AI team performance.

• Research and dissemination: Publish and present research findings at leading international conferences and journals, and collaborate with researchers across ELLIS Alicante, the ELLIS network, and external research partners.
• Training and project contributions: Contribute to the organization of an annual Training School on Trustworthy and Socially Aware Agentic AI, scientific project reporting, and the supervision and mentoring of PhD students.

The research may also address complementary topics, including norm-aware agent behavior and cooperation in multi-agent environments.

Required qualifications

Education and research experience

• PhD in Computer Science, Artificial Intelligence, Human–Computer Interaction, Cognitive Science, or a closely related field. Candidates who have completed their PhD or expect to complete it before the start date are welcome to apply.
• Strong research expertise in one or more relevant areas, such as human–AI interaction, human–AI collaboration, agentic AI, multi-agent systems, machine learning, or the empirical evaluation of AI systems.
• Strong programming skills and practical experience with modern machine learning frameworks, AI systems, or computational methods relevant to the research agenda.
• Experience in empirical research, including the design, execution, or analysis of experiments or user studies.
• A strong research track record, demonstrated through publications and other relevant research contributions appropriate to career stage.

Additional relevant experience

The following will be considered advantages:

• Experience developing, evaluating, or deploying LLM-based agents and multi-agent AI systems.
• Knowledge of experimental design, cognitive load measurement, behavioral analysis, or human decision-making.
• Experience with adaptive interfaces, mixed-initiative interaction, human–AI teaming, or research on trust and reliance in AI systems.
• Familiarity with trustworthy AI, fairness, responsible AI, or norm-aware agent behavior.
• Experience conducting longitudinal studies or analyzing complex human-subject data.
• Experience with project coordination, scientific dissemination, mentoring, or organizing academic events.

Candidates with publications at leading venues in relevant fields, such as NeurIPS, ICML, ICLR, ACL, AAAI, IJCAI, AAMAS, CHI, CSCW, IUI, ACM CHI, ACM CSCW, ACM/AAAI AIES and ACM FAccT, are particularly encouraged to apply.

Candidates are also encouraged to consult the ELLIS criteria for postdoctoral nominations: https://ellis.eu/nomination-phd-postdoc.

Personal skills and attributes

• Strong analytical, critical-thinking, and creative problem-solving skills.
• Ability to formulate research questions, develop original ideas, and pursue them independently.
• Excellent written and spoken English, including the ability to communicate complex research findings clearly.
• Strong interpersonal and collaboration skills, with the ability to work effectively in an interdisciplinary and international environment.
• Initiative, intellectual curiosity, sound research judgment, and a commitment to scientific integrity and responsible research.
• Motivation to contribute to a collaborative research culture and to the broader scientific community.