BIPD/ARIES-Health/2026

Universidade da Madeira; Portugal; On-site; EUR 19,000 - 23,000; Full time

Job summary

A Universidade da Madeira tem uma vaga de pós-doutoramento sob o projeto ARIES (ref. M2030-FEDER-03053400). A bolsa oferece condições conforme o regulamento da FCT, com duração inicial de 12 meses e possibilidade de renovação até 36 meses.

O protocolo envolve IA, VR e dados multimodais em ambiente HPC, com foco em reabilitação clínica. O(a) candidato(a) ideal tem doutoramento recente, experiência em IA, dados multimodais, e habilidade de trabalhar com dados sensíveis em contexto clínico.

Qualifications

• Doutoramento em área relevante para o plano de trabalho.
• Experiência com IA e análise de dados multimodais.
• Familiaridade com ambientes HPC e GPUs.
• Experiência prévia em projetos de investigação ou desenvolvimento tecnológico.
• Capacidade de comunicação oral/ escrita em inglês; básico em português.

Responsibilities

• Conduzir uma revisão de estado da arte sobre biomarcadores na monitorização de intervenções clínicas na reabilitação.
• Desenvolver um protocolo experimental para aquisição, processamento e integração de dados multimodais com infraestrutura local segura.
• Desenvolver e avaliar modelos de IA para identificar padrões de resposta clínica durante a reabilitação.
• Desenvolver métodos de adaptação dinâmica de intervenções de reabilitação com base nos sinais previstos pelo modelo.
• Avaliar o uso de VR com biofeedback adaptativo para personalizar tarefas e estímulos durante a reabilitação.
• Validar metodologias por estudos experimentais e disseminar resultados em revistas e conferências.

Skills

Inteligência Artificial

Análise de dados multimodais

Interfaces cérebro-computador

Education

Doutoramento em área relacionada

Tools

Desenvolvimento VR

Ambiente HPC/GPU

Job description

Organisation/Company Universidade da Madeira Research Field Other Researcher Profile First Stage Researcher (R1) Positions Postdoc Positions Application Deadline 10 Nov 2026 - 23:59 (Atlantic/Madeira) Country Portugal Type of Contract Not Applicable Job Status Full-time Hours Per Week 35 Offer Starting Date 20 Oct 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

Offer Description

A call for applications is now open for the award of one (1) postdoctoral fellowship under the ARIES project (reference M2030-FEDER-03053400), funded by the IDR (Regional Development Institute), subject to the following conditions:

• I. Scientific Field: Computer Engineering, Human-Computer Interaction, or related fields.
• II. Admission Requirements:
  • a) General requirements:
    • a. The candidate must hold a doctoral degree, with an academic and scientific background demonstrating specialization relevant to the execution of the work plan;
    • b. The doctoral degree must have been obtained within the three years preceding the application submission date;
    • c. The postdoctoral research must be conducted at a host institution different from the one where the research leading to the doctoral degree was carried out;
    • d. The research activities do not require prior postdoctoral experience;
    • e. The research activities must have a duration/execution period of three years or less;
    • f. Upon entering into this fellowship agreement—including any potential renewals—the fellow must not exceed a cumulative total of three years (whether consecutive or non-consecutive) in this type of fellowship.
  • b) Preferred requirements:
    • a. Experience with brain-computer interfaces and the processing of physiological signals.
    • b. Experience in AI and the analysis of multimodal data.
    • c. Experience working in high-performance computing (HPC) environments and using GPUs.
    • d. Relevant prior experience in programming VR applications for rehabilitation;
    • e. Relevant prior experience in collecting data from clinical populations;
    • f. Proficiency in oral and written English, and basic communication skills in Portuguese;
    • g. Prior experience in research or technological development projects;
    • h. Knowledge of data privacy and security, particularly regarding the handling of sensitive information.
• III. Work plan:
  • Conduct a state-of-the-art review on biomarkers applied to the monitoring, assessment, and optimization of clinical interventions in the field of rehabilitation.
  • Develop an experimental protocol for the acquisition, processing, and integration of multimodal data, utilizing a local computational infrastructure to ensure the security of users' sensitive medical data.
  • Develop and evaluate AI models to identify patterns associated with individual responses and clinical progression during the rehabilitation process.
  • Develop methods for the dynamic adaptation of rehabilitation interventions, adjusted based on user performance and progress, using predictions generated by the AI models.
  • Evaluate the impact of using VR with adaptive biofeedback on the customization of tasks, stimuli, and difficulty levels presented during rehabilitation.
  • Experimentally validate the implemented methodologies through experimental studies.
  • Dissemination of results through scientific publications in journals/conferences within the field.
• IV. Applicable legislation and regulations: The Research Fellowship Statute (in its current version), the University of Madeira’s Research Fellowship Regulations, and the FCT, I.P. Research Fellowship Regulations (in their current version).
• V. Workplace: The work will be carried out at the BIESA Lab, under the scientific supervision of Professor Fernando Manuel Rosmaninho Morgado Ferrão Dias.
• VI. Duration of the fellowship: The fellowship will have an initial duration of 12 months. The fellowship contract may be renewed for equal periods, up to a maximum of 36 months or until the end of the project in 2029.
• VII. Monthly maintenance allowance: The fellowship amount is €1,901, in accordance with the table of values for fellowships awarded directly by the FCT, I.P. within the country.
• VIII. Funding: The fellowship granted under this call will be funded by the European Regional Development Fund (ERDF), through the Madeira Regional Programme 2021–2027 (Madeira 2030), Portugal 2030, and the European Union | Operation Code: M2030 FEDER03053400.
• IX. Selection methods: The evaluation criteria to be applied are as follows:
  • Curricular evaluation (60%): This will take into account the letter of motivation (10%), academic training, and its suitability for the position. (30%), and relevant prior experience (20%).
  • Interview (40%).
• X. Composition of the Selection Committee:
  • Chair of the Committee: Prof. Dr. Sergi Bermúdez i Badia
  • Full Member: Prof. Dr. Fernando Manuel Rosmaninho Morgado Ferrão Dias
  • Full Member: Prof. Dr. Mônica Cameirão
  • Alternate Member: Prof. Dr. Rodrigo Lima
• XI. Method of publication/notification of results: Admission lists, as well as the results of each selection method and the final ranking lists, will be published on the website of the Human Resources Unit – Scholarship Office (Núcleo do Bolsista) of the University of Madeira (http://urh.uma.pt/ ), and candidates will be notified via email.
• XII. Application period and submission procedure:
  • a) Applications may be submitted within 15 business days following the publication of this Call;
  • b) Applications must be formalized by submitting an application letter, accompanied by the following documents:
    • Motivation letter;
    • Curriculum Vitae;
    • Certificate of qualifications.
  • c) Applications may be delivered in person between 09:00 and 12:30 and between 14:00 and 17:30 at the Human Resources Unit – Scholarship Office (Núcleo do Bolsista) of the University of Madeira, located at Colégio dos Jesuítas, Rua dos Ferreiros, 9000-081 Funchal; alternatively, they may be sent by mail to the same department and address, or via email to [e-mail] , addressed to the Chair of the Selection Committee, with the scholarship reference included in the subject line.