Ubicación: Sant Cugat del Vallès (España)
Tipo de Contrato: Beca
Jornada laboral: Jornada completa
Sector: Salud
Vacantes: 1
Modalidad de trabajo: PresencialMore than a job, a project.
About UIC Barcelona
UIC Barcelona is home to over 8,000 students and offers 16 bachelor’s degree programmes, 26 international double degrees and a wide range of master's and postgraduate degrees, in addition to continuing education courses in different fields of knowledge. Since 1997, we have been teaching people based on academic rigour, a
fulfilling university life and enriching life experiences. The UIC Barcelona team is made up of professionals who are qualified not only in the field of teaching, but also in research, management, administration, communication, services and systems. Beyond the professionalism of each individual, at UIC Barcelona you will find a young and dynamic working atmosphere.
The project
Universitat Internacional de Catalunya (UIC Barcelona) is looking for a predoctoral fellow to work on a project funded by Fundación la Caixa (“Ús del machine learning per
identificar els determinants i el risc de suïcidi en joves”, ref: CX23-00254). The project aims to identify clinical and social determinants associated with emotional distress in
young people, isolate warning signs and precursors of suicidal behavior, and develop
automated classification metrics for clinical use. It will analyze anonymized text data from a youth emotional support chat service using Natural Language Processing (NLP)
techniques to classify risk levels and detect early signs of suicidal behavior.
About your role
The elected candidate will apply to STEP- FI fellowship. During the project, the predoctoral fellow will analyze text data from youth support services using NLP techniques to classify risk levels of emotional distress and suicidal behavior. He/She will develop and validate machine learning models to detect early warning signs. The fellow will collaborate with mental health experts, ensuring ethical data handling and clinical relevance of the results.
Characteristics of the predoctoral candidate:
• Strong background in computer science or computational linguistics
• Experience in NLP techniques and machine learning algorithms
• Experience with deep learning frameworks (e.g., BERT, LSTM, GRU)
• Knowledge of text classification and sentiment analysis
• Familiarity with mental health topics, particularly suicide prevention would be a plus
• Data preprocessing and quality control skills
• Excellent programming skills, particularly in Python
• Good understanding of research methodologies and statistical analysis
Assessment criteria
The following aspects of the applicant's CV will be considered:
Professional knowledge and experience. (75%)
The ability to undertake mentored research with a high degree of independence. Special attention will be paid to applicants who have made valuable contributions in the area of applied machine learning (50%).
Knowledge in mental health and/or suicide prevention (40%):
Proficiency in speaking and writing in English (10%).
Competences (25%)
Initiative, commitment and communication skills (20%).
The ability to work independently and as a member of a diverse team (20%).
Flexibility and adaptability (20%).
Management skills (20%).
Oral and written ability in English and/or Spanish and/or Catalan (20%).
Specific Requirements
Master and bachelor’s degree in Statistics, Psychology, Biomedicine, Biology, or other
related degrees with high programming and statistical content.
Advanced knowledge in bioinformatics and statistics.
Programming skills in at least one statistical software (R, Python, etc.).
Good writing and communication skills in English.
The gross salary is €23,673.75 in the first year, increasing to €30,916.85 in the third year, plus an additional €12,000 for training expenses.
Interested persons should contact at: pcastellvi@uic.es; ioliveras@uic.es
