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Unique identifier: 34c4e656-acb0-4549-b152-8328a0ba1af7

1. Descrição do cargo/posição/bolsa
1. Job description

Research Grant (BI)

Job/Fellowship Reference: BI-DEBAQI-NETSCI

Main research field: Computer science

Sub research field: Informatics

Job summary:

One fully funded research grant for a PhD candidate with a relevant Master's degree to work in a team led by Prof. Manuel Pita (PI) at the Centre for Research in Applied Communication, Culture and New Technologies (CICANT, Universidade Lusófona, Lisbon, Portugal), and co-supervised by Prof. Luis Rocha (Indiana University, USA, and Instituto Gulbenkian de Ciência, Portugal). The research field is in the area of Artificial Intelligence advanced Recommender Systems and dynamic, web-based, Information Visualisation. This PhD student grant is supported by the project DSAIPA/DS/0102/2019: Factors to Promote Healthy Dialogue and Behaviours in Online School Communities , funded by the Portuguese Foundation for Science and Technology (FCT).

Job description:

The main goal of the research project is to develop a cutting-edge analytics platform that integrates Natural Language Processing (NLP), Network Science and Artificial Intelligence to process large text datasets produced by students that participate in regular debates online. This engine will support the Ministry of Education decision makers, specifically at the Network of School Libraries (RBE) in devising ethical educational interventions to improve critical thinking skills, engagement in plural conversations and thus counteract phenomena such as hate speech, polarisation and the spread of fake-news. The successful grantee will be mentored by the PI as well as by a team of world-renowned experts, of particular interest to this position, Prof. Luís Rocha (Indiana University and Instituto Gulbenkian de Ciência), who is the Co-PI of the project.
Candidate’s profile
  • Master’s degree or similar in Computer Science, Mathematics, Artificial Intelligence, similar degree, or equivalent qualifications;
  • Solid programming skills in Python, R, Java and/or similar languages;
  • Knowledge of network analysis techniques (e.g. graph theory, information theory, SNA, network science);
  • Background in multivariate statistics, and other statistical analysis methods, including computational implementation in e.g. Python and/or R;
  • Background and/or experience as a Software Engineer;
  • Previous experience with Data Science and AI techniques, esp. classifier/regression models, machine learning, genetic algorithms and/or similar;
  • A keen interest in being mentored in the use of network science methods to identify the loci of control and information processing in complex networks dynamics through data analysis and model construction;
  • The successful candidate must be fluent in English (both written and spoken);
  • Good command of the Portuguese language is highly desirable but not strictly required.

Applicable laws and regulations
Candidates not fulfilling the areas of knowledge requirements will be directly excluded. Applicants with foreign academic degrees must present Certificate of Level Recognition in accordance with applicable law or a proof that the recognition process is ongoing. Applicable Legislation and Regulations: Scientific Research Grant Holder Statute, approved by Law No. 40/2004 of August 18, amended and republished by Decree-Law No. 202/2012 of August 27, by Decree-Law No. 89/2013 of 9 July, by Decree-Law No. 233/2012 of October 29, and by Law No. 12/2013 of January 29, and amended by Decree-Law No. 123/2019 of August 28, as amended (https: //www.fct.pt/apoios/bolsas/estatutobolseiro) and FCT, I. P Research Fellowship Regulation, in force (https://www.fct.pt/apoios/bolsas/regulamento.phtml.pt).
Work place, stipend and grant duration
The successful grantee will be based at CICANT (Universidade Lusófona) and Instituto Gulbenkian de Ciência (IGC, Oeiras, Portugal) and will work collaboratively with the team at INESC-ID Instituto Superior Técnico (Lisboa, Portugal). The grant has an initial duration of six months, that may be extended until the end of the project in January 2023 in accordance with in article 6, number 4 of the FCT regulations for research grants. The grant’s monthly stipend is EURO 1064 according to the current FCT’s stipends table (https://www.fct.pt/apoios/bolsas/docs/RegulamentoBolsasFCT2019.pdf).
Application submission, selection criteria and publishing results
The selection method will consider the candidate’s CV and motivation letter (60%) and face-to-face interview (40%) for a final score (100%). The Jury is constituted by Dr. Manuel Pita, Dr. Miguel Won, Prof. Bruno Martins and Prof Luís Rocha. Applications must include CV, motivation letter and appropriate certificates.

Applications must be sent by e-mail to manuel.pita@ulusofona.pt using as subject:
“BI-DEBAQI-NETSCI Application”.

Submissions are open from September 7th 2020 until September 21st 2020. The final results of the evaluation will be publicised, through a list of candidates, ordered by final score obtained. Candidates will be notified of results via email.

To comply with FCT's regulation nº950/2019 of December 16th, 2019, articles 3rd and 6th, the successful candidate must be enrolled in an educational program leading to an academic degree, in this case a PhD, prior to becoming the recipient of this grant. For any questions about this requirement please contact Prof. Manuel Marques-Pita manuel.pita@ulusofona.pt
We are committed to positive grantee selection policies to promote equal opportunity regardless of race, age, gender, sexual orientation, marital status, ethnic origin, nationality, religion or disability. As an equal opportunities university and research centre we do not discriminate on any grounds other than ability to carry out the work. Our philosophy is to ensure that ability, contribution to science with a positive social impact, and potential for individual and team development are the determining factors in the selection of the successful grantee.

Vacant posts: 1

Type of contract: Temporary

Job country: Portugal

Job city: Lisbon

Job company/institute: Universidade Lusófona. CICANT

Application deadline: 21 Setembro 2020
(The Application's deadline must be confirmed on the Job Description)

2. Dados de contactos da organização
2. Organization contact data

Organization/institute: Universidade Lusófona de Humanidades e Tecnologias

Campo Grande 376
Lisboa - 1750-240

Email: manuel.pita@ulusofona.pt

Website: http://cicant.ulusofona.pt/

3. Habilitações académicas
3. Required education Level

Degree: Master's degree or equivalent qualification.
Degree field: Computer science
4. Línguas exigidas
4. Required languages

Language: English
Priority: High
Reading: Excelent
Writing: Good
Comprehension: Excelent
Conversation: Excelent
5. Experiência exigida em investigação
5. Required research experience