Natural language processing (NLP) received a strong push in the last decade, due to the abundance of web data, and leveraging advances on statistical machine learning. While many different NLP tasks have seen significant progress, issues like (a) handling figurative devices (e.g., irony or metaphor) in written text, or (b) document-level parsing of discourse and/or argumentation structures, remain significantly challenging.
Discourse parsing requires understanding the communicative/argumentative roles of sentences or parts of a document, as well as their relationships. For that, typical features related to words and simple syntax cues are clearly insufficient, and mechanisms like understanding interactivity, coherence and thematic development are required. These difficulties motivate additional research towards building better representations for the text, that can then be explored by machine learning methods.
Discourse parsing is closely related to argumentation mining from text, a challenge that only recently has come to the attention of NLP researchers. Many important challenges remain open, particularly if we consider text that are not essentially argumentative, related with existing heterogeneous argumentative styles. Argumentation involves a large and heterogeneous set of linguistic representations humans have at their disposal. Argumentation processes have been studied in diverse areas (e.g., philosophy, linguistics, or even artificial intelligence); on the other hand, NLP approaches for argumentation mining are relatively scarce in the literature, particularly for other languages besides English.
The Discourse Analysis and Argumentation Mining from Text Sources (DARGMINTS) project proposes to study NLP/IE techniques for addressing the task of argument mining from text, focusing on the Portuguese language (for which there is no relevant prior work), considering sources such as (a) news articles, (b) parliamentary debate transcriptions, and (c) discussions in specific social network profiles. The development of an NLP pipeline for the Portuguese language will be carried on, leveraging recent advances in the area. This NLP pipeline will support more advanced tasks, related to document-level parsing of discourse and to mining argument structures, to be aligned with argumentation schemes and discourse theories.
We also envision the development of new interactive visualizations for exploring argumentation patterns and processes. Such visualizations will be the basis for building appealing applications, that resort to different types of textual sources (news, parliamentary debate or on-line discussion archives), in areas related with media studies, political science or forensics (e.g. identifying opinion makers, detecting fallacies or radicalization processes), as well as applications specifically tailored for researchers in applied linguistics.
Within the DARGMINTS project, the researcher that is to be hired will broadly work on all the tasks that were considered in the project, although with a specific focus on deep learning methods for natural language processing, particularly addressing cross-language and transfer-learning methods for applications related to argumentation mining from text.

Innovative geographic knowledge discovery is becoming increasingly possible through the analysis of large-scale data, for instance made available by Earth observation projects leveraging satellites and remote-sensing, provided by ground-level sensors, or given as volunteered geographical information (e.g., geo-referenced multimedia contents posted online on social media platforms). However, problems that involve combining remotely-sensed data with volunteered geographical information are only now starting to be explored, and they still involve a number of practical challenges, e.g. related to appropriate content classification.
Over the recent years, data classification leveraging deep neural networks has also become increasingly popular. These methods have been reported to result in impressive performance gains, when applied to problems related to processing images or natural language. Within GIScience research, deep learning can also have several applications, that are only now starting to be explored (e.g., for improving land coverage analysis, spatial downscaling methods, and general classification tasks that involve combining different types of data).
Within the MIMU project (i.e., acronym for MIning MUlti-source and MUlti-modal geo-referenced information), the researcher that is to be hired will work on the use of machine learning approaches for the discovery and mapping of innovative geographic knowledge through the analysis and processing of large-scale volunteered data (e.g., geo-referenced multimedia contents such as images and textual descriptions, posted on social-media platforms like Flickr, Twitter, or Foursquare), in combination with more traditional sources (e.g., remote- sensing products available in the context of initiatives like ESA's Sentinel/Copernicus programme, and/or tables with socio-demographic data made available by statistical offices). The complex relations between the different types of information, as well as the temporal and geographical dimensions of the data, introduce new challenges that will explored throughout the project, in an attempt to go beyond the current state-of-the-art.

One research grant(s)  Bolsa de Investigacão - Mestre is now available in project SARRROCA, “Synthetic Aperture Radar Robust Reconfigurable Optimized Computing Architecture” - ref: PTDC/EEI-HAC/31819/2017 funded by FCT/MCTES through national funds, and, where appropriate, POCI - Programa Operacional Competitividade e Internacionalização e PORLisboa – Programa Operacional Regional de Lisboa, under the following conditions:
Duration
Six months from 1 of October 2019. The grant may be renewed within the period of the project, not exceeding the maximum period set by FCT for such grants. Renewal is subject to suitable performance
Legislation
A fellowship contract will be celebrated according to the Regulations for Research Grants of the Foundation for Science and Technology in force the INESC ID Grant regulations approved by FCT, and to the Status of Scientific Research Fellow (Lei nº 40/2004 de 18 de Agosto, and its successive amendments).
Monthly amount
The monthly amount of the grant 989,70€ is in accordance with the values stipulated in the “Regulations for Research Grants of the Foundation for Science and Technology” in force (https://www.fct.pt/apoios/bolsas/regulamentos.phtml.pt) and (http://www.fct.pt/apoios/bolsas/valores) and INESC-ID Lisboa Grant Regulations approved by FCT, and shall be rendered through a monthly bank transfer to an account held by the grantee
Objectives / summary
This research work aims to develop a fault-tolerant embedded system using Xilinx FPGAs. The research work will involve designing novel hardware architectures and study and implementation of adequate fault-tolerant mechanisms. Expected outputs of this work are the implementation of prototypes for real-time fault-tolerant architectures.
Required education Level and research experience
The candidate should have an MSc degree in Computer Science and Engineering, or Electrical and Electronic Engineering and research project experience in System on a Chip design using FPGAs from Xilinx.  The candidate should be familiarized with most common fault-tolerance mechanisms on FPGAs. Language skills - proficiency in English. Preference will be given to candidates willing to pursue a PhD degree.

One research grant(s)  Bolsa de Investigacão - Mestre is now available in project SARRROCA, “Synthetic Aperture Radar Robust Reconfigurable Optimized Computing Architecture” - ref: PTDC/EEI-HAC/31819/2017 funded by FCT/MCTES through national funds, and, where appropriate, POCI - Programa Operacional Competitividade e Internacionalização e PORLisboa – Programa Operacional Regional de Lisboa, under the following conditions:
Duration
Six months from 1 of October 2019. The grant may be renewed within the period of the project, not exceeding the maximum period set by FCT for such grants. Renewal is subject to suitable performance
Legislation
A fellowship contract will be celebrated according to the Regulations for Research Grants of the Foundation for Science and Technology in force the INESC ID Grant regulations approved by FCT, and to the Status of Scientific Research Fellow (Lei nº 40/2004 de 18 de Agosto, and its successive amendments).
Monthly amount
The monthly amount of the grant 989,70€ is in accordance with the values stipulated in the “Regulations for Research Grants of the Foundation for Science and Technology” in force (https://www.fct.pt/apoios/bolsas/regulamentos.phtml.pt) and (http://www.fct.pt/apoios/bolsas/valores) and INESC-ID Lisboa Grant Regulations approved by FCT, and shall be rendered through a monthly bank transfer to an account held by the grantee
Objectives / summary
This research work aims to develop a fault-tolerant embedded system using ARM/AVR/Arduino devices. The research work will involve designing novel hardware architectures and study and implementation of adequate fault-tolerant mechanisms. Expected outputs of this work are the implementation of prototypes for real-time fault-tolerant architectures.
Required education Level and research experience
The candidate should have an MSc degree in Computer Science and Engineering, or Electrical and Electronic Engineering and research project experience in embedded systems.  The candidate should be familiarized with Arduino and ARM platforms. The candidate should also demonstrate experience in sensors and actuators connected to an Arduino. Language skills - proficiency in English.  Preference will be given to candidates willing to pursue a PhD degree

Job summary: 
Within project “Skeletal TRacking Enhanced with Anatomically Correct Kinematics for Exergames and Rehabilitation (STREACKER)” the awardee will perform two main tasks: (1) testing and training the machine learning algorithm given the acquired data sets; and (2) contribute to implement efficient for the skeletal tracking algorithm. The awardee will also contribute to validate the machine learning algorithm. Additional tasks include performing Requirement Analysis within clinical scenarios and conducting user studies will also be demanded.
Job description:
Research Grant
BI-Mestre Studentship
STREACKER - UTAP-EXPL/CA/0065/2017
The Instituto de Engenharia de Sistemas e Computadores, Investigação e Desenvolvimento em Lisboa (INESC-ID) Portugal is one of the largest and most dynamic research institutes in Portugal in the areas of Computing Systems and Communication Networks, Embedded Electronic Systems, Information and Decision Support Systems, Interactive Intelligent Systems and Energy Systems.
1 research grant BI-Mestre Studentship is now available in project STREACKER - UTAP-EXPL/CA/0065/2017 funded by FCT/MCTES through national funds, under the following conditions:
Duration
4 months from May 24, 2019. This grant is not renewable.
Legislation
A fellowship contract will be celebrated according to the Regulations for Research Grants of the Foundation for Science and Technology in force the INESC ID Grant regulations approved by FCT, and to the Status of Scientific Research Fellow (Lei nº 40/2004 de 18 de Agosto, and its successive amendments).
Monthly amount
The monthly amount of the grant €989,70 is in accordance with the values stipulated in the “Regulations for Research Grants of the Foundation for Science and Technology” in force (https://www.fct.pt/apoios/bolsas/regulamentos.phtml.pt) and (http://www.fct.pt/apoios/bolsas/valores) and INESC-ID Lisboa Grant Regulations approved by FCT, and shall be rendered through a monthly bank transfer to an account held by the grantee
Objectives / summary
Within project “Skeletal TRacking Enhanced with Anatomically Correct Kinematics for Exergames and Rehabilitation (STREACKER)” the awardee will perform two main tasks: (1) testing and training the machine learning algorithm given the acquired data sets; and (2) contribute to implement efficient for the skeletal tracking algorithm. The awardee will also contribute to validate the machine learning algorithm. Additional tasks include performing Requirement Analysis within clinical scenarios and conducting user studies will also be demanded.
Scientific supervision
The activity will be supervised by Daniel Simões Lopes, Assistant Professor at Instituto Superior Técnico, Universidade de Lisboa, and head of Biomedical Research at VIMMI/INESC-ID. The grantee will be integrated at INESC-ID Lisboa, in the Visualization and Intelligent Multimodal Interfaces Group (https://www.inesc-id.pt/group/II07) and will develop his work at the JLF Lab in the Taguspark Campus.
Required education Level and research experience
The candidate should hold a MSc in Computer Science, Electrical Engineering, Biomedical Engineering or related areas. Language skills - proficiency in English.
Evaluation criteria
Academic record of the candidate (25%) and interest for the following areas of research Machine Learning (10%), Biomechanics (20%), and Human-Computer Interaction (10%). Experience in scientific writing is mandatory (35%). The Juri will interview the top 3 candidates with higher classification. In order to perform a more objective evaluation of some of the criteria, the interview will count for 50% of the evaluation of each criteria above.
The jury will convene in May 23rd and is composed of
Name /Professional Status / Institution
Daniel Simões Lopes / Assistant Professor/Instituto Superior Técnico
Hugo Miguel Aleixo Albuquerque Nicolau / Assistant Professor/Instituto Superior Técnico
Joaquim Armando Pires Jorge / Full Professor/Instituto Superior Técnico
Results
The final evaluation results will be publicized through an ordered list, and the candidates will be notified of the Jury decision by email.
Formalisation of applications
Applications are formalised by sending an email to daniel.lopes@inesc-id.pt with the documents stated bellow.  The application email should clearly state the reference of the project.
detailed curriculum vitae
motivation letter
single copy of official academic degree certificate with detailed list of grades, required in education level.
name of two personal references
*For candidates with degrees granted by foreign higher education institutions it is mandatory to have a degree or diploma recognition.  For more information press here.
 
Application Dates
 From May 7th, 2019 to May 21st, 2019

1 research grant BI-Mestre Studentship is now available in project Augmenting Rehabilitation Centres with Context-Aware Digital Environments (ARCADE - PTDC/CCI-COM/30274/2017) funded by FCT/MCTES through national funds, and, where appropriate, POCI - Programa Operacional Competitividade e Internacionalização e PORLisboa – Programa Operacional Regional de Lisboa, under the following conditions:
Duration 
12 months from April 1st, 2019. The grant may be renewed within the period of the project, not exceeding the maximum period set by FCT for such grants. Renewal is subject to suitable performance
Legislation
A fellowship contract will be celebrated according to the “Regulations for Research Grants of the Foundation for Science and Technology” in force (https://www.fct.pt/apoios/bolsas/docs/RegulamentoBolsasFCT2018.pdf)  the INESC ID Grant regulations approved by FCT, and to the Status of Scientific Research Fellow (Lei nº 40/2004 de 18 de Agosto, and its successive amendments).
Monthly amount 
The monthly amount of the grant 980€ is in accordance with the values stipulated in the “Regulations for Research Grants of the Foundation for Science and Technology” in force (http://www.fct.pt/apoios/bolsas/docs/RegulamentoBolsasFCT2018.pdf) (http://www.fct.pt/apoios/bolsas/valores) and INESC-ID Lisboa Grant Regulations approved by FCT, and shall be rendered through a monthly bank transfer to an account held by the grantee
Objectives / summary
The awardee will perform two main tasks: (1) Develop interactive applications for stroke patients that leverage data from inertial sensors placed on rehabilitation objects, and (2) Develop tools that support physiotherapists' activities in clinical rehabilitation settings. Both tasks will follow user-centered design methodologies. We will use inertial sensors and follow an approach of “tape on and forget” that can be quickly and ubiquitously installed in clinical rehabilitation settings to augment existing “dumb” equipment.
Scientific supervision
The activity will be supervised by Prof. Hugo Miguel Aleixo Albuquerque Nicolau, Principal Investigator, Assistant Professor at Instituto Superior Técnico, researcher at INESC-ID Lisboa. The grantee will be integrated at INESC-ID Taguspark in the Visualization and Intelligent Multimodal Interfaces Group (https://inesc-id.pt/group/II07/).
Required education Level and research experience
The candidate should have an MSc in Computer Science, Biomedical Engineering, Electrical Engineering or related areas. Preference will be given to candidates that have a strong Human-Computer Interaction background. The ideal candidate should have working knowledge of User-Centred Design methodologies, Computer Graphics, experience with object-oriented programming and skilled in Unity3D.
Language skills - proficiency in English
Evaluation criteria 
The academic record of the candidate and interest for the following areas of research Human-Computer Interaction (40%), Interactive Rehabilitation Applications (40%), and Inertial Sensors (20%). The Jury will interview the top 3 candidates with higher classification.  In order to perform a more objective evaluation of some of the criteria, the interview will count for 50% of the evaluation of each criterion above.
The jury will convene on March 18th, 2019 and is composed of:
Hugo Miguel Aleixo Albuquerque Nicolau,	Assistant Professor, Instituto Superior Técnico
Daniel Simões Lopes, Assistant Professor, Instituto Superior Técnico
Joaquim Armando Pires Jorge, Full Professor, Instituto Superior Técnico
Results
The final evaluation results will be publicized through an ordered list, and the candidates will be notified of the Jury decision by email.
Documents to be submitted 
all applications should clearly state the reference of the project
1.	detailed curriculum vitae
2.	motivation letter
3.	copy of the official academic degree certificate, including a detailed list of grades **
4.	name of two personal references
**For candidates with degrees granted by foreign higher education institutions it is mandatory to have equivalence/recognition of the degree.
For more information please follow the links bellow
https://www.dges.gov.pt/pt/pagina/equivalencia-reconhecimento
https://www.ulisboa.pt/info/reconhecimento-de-habilitacoes-estrangeiras
Application Dates
From February 15th to March 15th, 2019
For further information and proposal submission, please contact
Hugo Nicolau, INESC-ID Lisboa, IST Taguspark, Room 2N9.21
Avenida Professor Cavaco Silva, 2744-016 Porto Salvo, Portugal, hman@inesc-id.pt

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