INESC TEC is accepting applications for 1 job(s) in the Research and development of new algorithms for processing and classifying physiological signals in ambulatory systems (AE2025-0604)

INESC TEC, Portugal

Updated: 22 days ago
Job Type: FullTime
Deadline: 21 Jan 2026

8 Jan 2026
Job Information
Organisation/Company

INESC TEC
Research Field

Computer science » Computer systems
Researcher Profile

First Stage Researcher (R1)
Country

Portugal
Application Deadline

21 Jan 2026 - 23:59 (UTC)
Type of Contract

Temporary
Job Status

Full-time
Hours Per Week

36
Offer Starting Date

9 Feb 2026
Is the job funded through the EU Research Framework Programme?

Not funded by a EU programme
Reference Number

AE2025-0604
Is the Job related to staff position within a Research Infrastructure?

No

Offer Description

Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2025-0604.pdf
CALL FOR APPLICATIONS: RESEARCHER
Job/position/grant:

Job reference: AE2025-0604 (CBER-Geral-CBER)
INESC TEC - Instituto de Engenharia de Sistemas e Computadores, Tecnologia e Ciência
Job/position/grant: RESEARCHER
City: Porto
Research field: Main: COMPUTER SCIENCE
Sub: Computer Systems

Job summary:

INESC TEC is accepting applications for 1 RESEARCHER job in the Research and development of new algorithms for processing and classifying physiological signals in ambulatory systems
Project:
Scientific Advisor: João Paulo Cunha
Start Date: from 2026-02-09 to
Location: INESC TEC, Porto, Portugal

Job description:

Work Area: Research and development of new algorithms for processing and classifying physiological signals in ambulatory systems
Project overview: Processing of physiological and inertial signals (pre-processing, filtering, feature extraction in the time, frequency, and time-frequency domains). Development and validation of machine learning and deep learning models; integration and analysis of data from wearable and clinical monitoring devices and clinical databases. Experimental evaluation of algorithms, development, and deployment. Support in data collection and documentation of the work performed.
Objectives: The Center for Biomedical Engineering Research (C-BER) has extensive experience in biomedical signal processing, particularly physiological signals from wearable devices. This position aims to research and develop methods for processing physiological signals, including inertial signals and other wearable sensors, for subsequent application of machine learning and deep learning methods and classification of health and wellness parameters. Data acquisition, as well as presentations, scientific publications, and technical reports are also part of the objectives of this position.

Academic Qualifications: Master's degree in Biomedical Engineering, Electrical Engineering, Computer Science, or a similar field.
Minimum profile required: Experience in biomedical signal processing.
Knowledge of machine learning/deep learning (e.g., classification, feature learning, neural networks).
Experience in scientific programming (e.g., Python and/or MATLAB) and code management tools.
Good knowledge of written and spoken scientific English.
Preference factors: Previous work in developing algorithms for signal processing and machine learning/deep learning techniques with physiological signals, namely ECG and inertial from human movement.;
Previous knowledge in collecting physiological data and managing and preparing it for analysis.;

Funding Entity:
Type of contract: Uncertain term contract
The hiring shall be governed by what is stipulated in the legislation in force regarding fixed individual employment contracts and by INESC TEC norms.

Selection criteria: The selection of the candidates will be based on the following criteria, in descending order of consideration:
a) Relevant Curriculum in the concerned field of this tender
b) Proven experience.
DISABILITY INCENTIVE

Candidates who present a degree of disability equal to or greater than 90% will benefit from an incentive (20) in the score of the CV Assessment.
Candidates who present a degree of disability equal to or greater than 60% and less than 90% will also benefit from an incentive (10) in the score of the CV Assessment.
Said score may, in these cases, exceed 100 points.
Candidates must demonstrate the degree of disability during the application, namely through the submission of the Multi-Purpose Medical Certificate of Disability, issued in accordance with Decree-Law no. 202/96, of October 23 - currently in effect.

Selection Jury: President of the Jury: João Paulo Cunha
Member: Susana Cristina Rodrigues
Member: Miguel Velhote Correia
Substitute member: Miguel Coimbra

Notification of results: The results of the selection process will be sent to the interested by electronic mail.
Application period: From 2026-01-08 to 2026-01-21.
Application submission: Electronic form filling in www.inesctec.pt in the section Work with Us .


Where to apply
Website
https://www.inesctec.pt/en/opportunity/AE2025-0604

Requirements
Research Field
Computer science
Education Level
Master Degree or equivalent

Specific Requirements

Academic qualifications: Master's degree in Biomedical Engineering, Electrical Engineering, Computer Science, or a similar field.
Minimum profile: Experience in biomedical signal processing., Knowledge of machine learning/deep learning (e.g., classification, feature learning, neural networks)., Experience in scientific programming (e.g., Python and/or MATLAB) and code management tools., Good knowledge of written and spoken scientific English.
Preference factors: Previous work in developing algorithms for signal processing and machine learning/deep learning techniques with physiological signals, namely ECG and inertial from human movement.;
Previous knowledge in collecting physiological data and managing and preparing it for analysis.;
.


Research Field
Computer science » Computer systems
Years of Research Experience
None

Additional Information
Selection process

Selection criteria: The selection of the candidates will be based on the following criteria, in descending order of consideration:
a) Relevant Curriculum in the concerned field of this tender
b) Proven experience.
DISABILITY INCENTIVE

Candidates who present a degree of disability equal to or greater than 90% will benefit from an incentive (20) in the score of the CV Assessment.
Candidates who present a degree of disability equal to or greater than 60% and less than 90% will also benefit from an incentive (10) in the score of the CV Assessment.
Said score may, in these cases, exceed 100 points.
Candidates must demonstrate the degree of disability during the application, namely through the submission of the Multi-Purpose Medical Certificate of Disability, issued in accordance with Decree-Law no. 202/96, of October 23 - currently in effect.

Selection Jury: President of the Jury: João Paulo Cunha
Member: Susana Cristina Rodrigues
Member: Miguel Velhote Correia
Substitute member: Miguel Coimbra

Notification of results: The results of the selection process will be sent to the interested by electronic mail.
Application period: From 2026-01-08 to 2026-01-21.
Application submission: Electronic form filling in www.inesctec.pt in the section Work with Us .


Website for additional job details

https://www.inesctec.pt/en/opportunity/AE2025-0604

Work Location(s)
Number of offers available
1
Company/Institute
INESC TEC
Country
Portugal
City
Porto
Postal Code
4200-465
Street
Campus da Faculdade de Engenharia da Universidade do Porto, Rua Dr. Roberto Frias

Contact
City

Porto
Website

http://www.inesctec.pt
Street

Campus da FEUP - Rua Dr. Roberto Frias
Postal Code

4200-465 Porto

STATUS: EXPIRED

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