Master's Student: Applied Statistics in Social Robotics (Mandatory internship only) - Luxembourg

Please note that: We will begin reviewing applications immediately upon receipt, and will continue to do so on a rolling basis until the position is closed; The student must be regularly enrolled at a university or higher education institution, and the internship must be a mandatory component of their program of study; The compensation for this internship is 812€/month + lunch vouchers. Background The master's project will be conducted within an interdisciplinary research initiative focused on the quantitative analysis of behavioural and interaction data collected during robot-assisted interventions. The study involves the use of a humanoid robot, an interactive educational robot designed to support learning and engagement in children with neurodevelopmental conditions. The project lies at the interface between clinical research, behavioural science, and applied data science, and involves close collaboration between clinicians, psychologists, engineers, and statisticians. The study generates longitudinal and multi-source datasets (including repeated measures and structured assessments), offering a rich framework for advanced statistical modelling, natural language processing, bayesian statistics, and data-driven inference. The student will be integrated within the Competence Center for Methodology and Statistics, part of the Department of Medical Informatics, and will contribute to ongoing analyses supporting current and forthcoming research outputs. Objectives The main objective of this Master thesis internship is to support the quantitative analysis of the humanoid robot data, with a focus on transforming complex and longitudinal datasets into interpretable statistical results. Specific objectives include: Structuring, cleaning, and documenting the study datasets; Performing descriptive and inferential statistical analyses; Exploring longitudinal and repeated-measures modelling approaches; Contributing to the interpretation and visualisation of results; Producing a Master thesis based on applied statistical analysis, with potential contribution to scientific dissemination. The precise scope of the thesis will be adapted to the student's background and academic requirements, in agreement with the home university supervisor. Training and Research Environment The intern will be supervised by Dr. Eduardo Rosales Jubal, part of the Competence Center for Methodology and Statistics from the Department of Medical Informatics. The research environment is interdisciplinary and international, offering: Close methodological supervision; Exposure to real-world clinical and behavioural datasets; Participation in team meetings and scientific discussions; Interaction with researchers in statistics, psychology, medicine, and AI. Where required, the internship will be conducted in coordination with an academic supervisor at the student's home university, in accordance with Master thesis regulations. Key Accountabilities Support preparation, cleaning, and documentation of the study datasets; Conduct statistical analyses using Python, MATLAB (or equivalent statistical software);$ Contribute to data visualisation and reporting of results; Participate in project meetings and scientific discussions; Prepare figures, tables, and methodological descriptions for the Master thesis. Key Skills, Experience and Qualifications Enrolled in a Master's programme (e.g. statistics, data science, psychology, cognitive science, biomedical sciences, or related fields); Good statistical knowledge and hands-on experience with statistical software (Python, MATLAB, R); Good organisational skills; Excellent planning and communication skills, with the ability to work in complex, multidisciplinary teams; Sense of responsibility, autonomy, curiosity, flexibility, and respect of confidentiality; Ability to work with people from diverse academic and cultural backgrounds; Language skills: Fluency in English (written and spoken) is mandatory; knowledge of other languages used in Luxembourg is an asset. Application Applications will be reviewed on an ongoing basis. Suitable candidates may be invited to interview shortly after their application is received. The recruitment process will close once a suitable candidate has been identified. To apply, please send: CV; Short motivation paragraph or letter; Transcript of records (if available); Indication of preferred start window (April or September). Gender equality The LIH is an equal opportunities employer. We are fully committed to removing any discriminatory barrier related to gender, and not only, in recruitment and career progression of our staff. The LIH is attentive to gender representation among its leadership staff and aims to eliminate obstacles to recruitment and promotion of female leaders and the...

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