07/09/2021

ONE research grant for candidates with MSc degree with reference number BI|2021/199 is now available under the scope of project INTELLIGENTCARE


  • ORGANISATION/COMPANY
    INESC ID
  • RESEARCH FIELD
    Engineering
  • RESEARCHER PROFILE
    First Stage Researcher (R1)
  • APPLICATION DEADLINE
    22/09/2021 23:00 - Europe/London
  • LOCATION
    Portugal › Lisboa
  • REFERENCE NUMBER
    INTELLIGENTCARE - REF. 45948 - BI|2021/199

OFFER DESCRIPTION

Public notice for research grant

INTELLIGENTCARE – INTELLIGENT MULTIMORBIDITY MANAGEMENT SYSTEM, CONCURSO AAC 04/SI/2019 DO PROGRAMA INTERFACE/CMU-PORTUGAL.

REF. 45948

INESC-ID - Instituto de Engenharia de Sistemas e Computadores, Investigação e Desenvolvimento em Lisboa is a R&D institute dedicated to advanced research and development in the fields of Information Technologies, Electronics, Communications, and Energy. INESC-ID has participated in more than 50 research projects funded by the European Union and more than 190 funded by national entities. Until today, our researchers have published more than 700 papers in international journal papers, more than 3000 papers in international conferences, and have registered 15 patents and/or brands.

1 | RESEARCH GRANT TYPE

ONE research grant for candidates with MSc degree with reference number BI|2021/199 is now available under the scope of project INTELLIGENTCARE – INTELLIGENT MULTIMORBIDITY MANAGEMENT SYSTEM, CONCURSO AAC 04/SI/2019 DO PROGRAMA INTERFACE/CMU-PORTUGAL., FUNDED BY THE APPLICABLE FINANCIAL FRAMEWORK., by FEDER, PROGRAMA OPERACIONAL REGIONAL DE LISBOA , AGÊNCIA NACIONAL DE INOVAÇÃO and CMU and under the following conditions:

2 | DURATION

6 months, starting in October 2021

- Renewable, if the candidate is enrolled in a PhD program - art. 6º, n.4 c)

(https://www.fct.pt/apoios/bolsas/docs/RegulamentoBolsasFCT2019.pdf )

subject to suitable performance within the period of the project, not exceeding the maximum period set by FCT for such grants – 4 years (included contract renewals)

- Renewable, if the candidate is enrolled in a non-degree programme – art. 6º, n. 4 a)

(https://www.fct.pt/apoios/bolsas/docs/RegulamentoBolsasFCT2019.pdf )

subject to suitable performance within the period of the project, not exceeding the maximum period set by FCT for such grants – 1 year (included contract renewals)

3 | LEGISLATION

A fellowship contract will be celebrated according to:

  1. Law 40/2004 of 18th of August (Scientific Research Fellow Status) and its successive amendments, including the amendments introduced by the Decree Law n. 123/2019 of 28 th of August

    https://dre.pt/web/guest/legislacao-consolidada/-/lc/124281176/201912061112/73740605/diploma/indice?lcq=estatuto+do+bolseiro,

     

  2. Regulations for Research Grants of the Foundation for Science and Technology in force (https://www.fct.pt/apoios/bolsas/docs/RegulamentoBolsasFCT2019.pdf )

     

  3. INESC-ID Lisboa Grant Regulations

https://www.inesc-id.pt/scholarship-regulations/

The fellowship contract is awarded on an exclusive dedication basis – art. 5 of Scientific Research Fellow Status and art. 16 of Regulations for Research Grants of the Foundation for Science and Technology.

4 | MONTHLY AMOUNT

The monthly amount of the grant 1104,64 € 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/docs/Tabela_Valores_SMM_LOE_2021.pdf ) and shall be rendered through a monthly bank transfer to an account held by the grantee

5 | OBJECTIVES/WORKPLAN

IntelligentCare project develops a multimorbidity management decision support system focused on the patient's vision of value, i.e., achieving the outcomes that matter for patients. To this end, analytical methodologies to identify high risk multimorbidity patient groups, as well as to evaluate and define evidence-based clinical pathways associated with each patient group will be used. The project contributes to improved healthcare delivery through precision and personalized medicine and to contribute to market sustainability using new technologies. INESC-ID leads a project activity for identifying and and characterizing the main clusters of multimorbidity in clinical data. The applicant to be hired will join a team engaged in performing exploratory analysis of clinical data for clinical phenotyping and identification of most frequent representative groups iin multimorbidity, and investigation and exploration of different data mining algorithms supporting this task.

6 | SCIENTIFIC SUPERVISION

The activity will be supervised by Mário Jorge Costa Gaspar da Silva, Full Professor at Tecnico and researcher at INESC-ID, and Andreia Sofia Monteiro Teixeira, Assistant Professor at FCUL and External Collaborator at INESC-ID.

INESC ID will integrate the grantee in the research team of the scientific advisor.

7 | ADMISSION REQUIREMENTS

The candidates should have an MSc in Computer Engineering, Biomedical Engineering or equivalent scientific areas.

 

By the grant start date, the candidate must be enrolled in

  1. a PhD programme – art. 6º, n.1

    (https://www.fct.pt/apoios/bolsas/docs/RegulamentoBolsasFCT2019.pdf)

or

  1. a non-degree programme – art. 6º, n. 2

    (https://www.fct.pt/apoios/bolsas/docs/RegulamentoBolsasFCT2019.pdf )

Preferential factors:

preference will be given to candidates who have:

  • Excellent academic and practical background in programming, machine learning, and natural language processing.
  • Strong preference is given to candidates with sound knowledge of proficiency in programming in Python/R and libraries for Machine Learning and Deep Learning.

The candidate should have good knowledge of written and spoken English, be self-motivated and show initiative in solving problems.

8 | EVALUATION CRITERIA AND COMMITEE

The selection will be according to the following criteria:

  1. 20%: demonstrated knowledge and past practical experience in the application of data science methods and techniques for clinical data analysis relevant to the goals of the project, including text mining, biomedical ontologies, and machine learning.
  2. 40%: proficiency in programming in Python/R and libraries for Machine Learning and Deep Learning
  3. 40%: academic grades, previous research experience and publication record

 

The jury may also decide not to interview or assign the scholarship, if none of candidates meets the required conditions

Jury

name

Professional Status

Institutions

President

Mário Jorge Costa Gaspar da Silva

Reseacher / Full Professor

INESC ID | Tecnico Ulisboa

Member

Bruno Emanuel da Graça Martins

Reseacher / Assistant Professor

INESC ID | Tecnico Ulisboa

Member

Andreia Sofia Monteiro Teixeira

External Collaborator / Assistant Professor

INESC ID | FCUL

Substitute member

Susana de Almeida Mendes Vinga Martins

Reseacher / Associate Professor

INESC ID | Tecnico Ulisboa

Substitute member

Alexandre Paulo Lourenço Francisco

Reseacher / Associate Professor

INESC ID | Tecnico Ulisboa

 
 
 
 
 
 

9 | COMPLAIN AND APPEAL DEADLINES AND PROCEDURES

The jury has the faculty not to select a candidate who does not prove the requirements mentioned in required education Level and research experience

 

The admitted and excluded candidates will be notified by email of the final ranking list, including the copy of the Preliminary Report of the jury.

 

Prior Hearing and Deadline for Final Decision: After being notified, candidates have 10 working days to submit, if applicable, a formal rebuttal.

 

After that period, the jury notifies the candidates of the Final Report.

 

Excluded applicants may complain about the jury's final report for 15 working days after notification or appeal the jury's decision to the INESC ID Board of Directors for 30 working days after notification.

 

According to the Portuguese Law, a disabled candidate has a preference when in equal classification, which prevails over any other legal preference. Candidates must declare their respective degree of disability, the type of disability and the means of communication / expression to be used in the selection process, under the law.

10 | FORMALISATION OF APPLICATIONS

Applications are formalised by sending an email to rh@inesc-id.pt with the documents stated bellow and in pdf form.

The application email should clearly state the reference of the research grant and project.

 

 

1

Single copy of official academic degree certificate in the required education level

 

a) In the application submission, the candidates from portuguese education institutions may replace this document by a declaration of honour stating that they have the required academic degree.

 

 

  • It is mandatory for the approval of the fellowship contract that the selected candidate presents a single copy of the official academic degree certificate, required in education level

b) In the application submission, the candidates from foreigner education institutions may replace this document by a declaration of honour stating that they have the required academic degree.

 

 

  •  
  • It is mandatory for the approval of the fellowship contract that the selected candidate presents a single copy of the official diploma recognition, required in education level

 

 

  •  
  • For more information about diploma recognition please press here

 

 

 

2

Detailed list of grades (pdf form);

 

 

 

3

Proof of enrolment required on 7 a) or 7 b) (pdf form);

 

In the application submission, the candidates may replace this document by a declaration of honour stating that they are/will be enrolled required in 7 a) or 7 b)

 

 

  • It is mandatory for the approval of the fellowship contract that the selected candidate presents an official copy of the enrolment, required in 7 a) or 7 b)

 

 

 

4

Detailed curriculum vitae (pdf form);

 

 

 

5

Motivation letter explaining the interest in the position (pdf form);

 

 

 

6

Name of two personal references (pdf form).

 

 
 
 
 
 

Application Dates

From

To

09-09-2021

 

22-09-2021

More Information

Benefits

The monthly amount of the grant 1104,64 € 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/docs/Tabela_Valores_SMM_LOE_2021.pdf ) and shall be rendered through a monthly bank transfer to an account held by the grantee.

Eligibility criteria

preference will be given to candidates who have:

  • Excellent academic and practical background in programming, machine learning, and natural language processing.
  • Strong preference is given to candidates with sound knowledge of proficiency in programming in Python/R and libraries for Machine Learning and Deep Learning.

The candidate should have good knowledge of written and spoken English, be self-motivated and show initiative in solving problems.

Selection process

The selection will be according to the following criteria:

  1. 20%: demonstrated knowledge and past practical experience in the application of data science methods and techniques for clinical data analysis relevant to the goals of the project, including text mining, biomedical ontologies, and machine learning.
  2. 40%: proficiency in programming in Python/R and libraries for Machine Learning and Deep Learning
  3. 40%: academic grades, previous research experience and publication record

 

The jury may also decide not to interview or assign the scholarship, if none of candidates meets the required conditions

Additional comments

a) In the application submission, the candidates from portuguese education institutions may replace the official academic degree certificate by a declaration of honour stating that they have the required academic degree.

- It is mandatory for the approval of the fellowship contract that the selected candidate presents a single copy of the official academic degree certificate, required in education level

 

b) In the application submission, the candidates from foreigner education institutions may replace the official academic degree certificate by a declaration of honour stating that they have the required academic degree.

 - It is mandatory for the approval of the fellowship contract that the selected candidate presents a single copy of the official diploma recognition, required in education level

 - For more information about diploma recognition please press https://www.dges.gov.pt/en/pagina/degree-and-diploma-recognition

Offer Requirements

  • REQUIRED EDUCATION LEVEL
    Engineering: Master Degree or equivalent
  • REQUIRED LANGUAGES
    ENGLISH: Good

Skills/Qualifications

IntelligentCare project develops a multimorbidity management decision support system focused on the patient's vision of value, i.e., achieving the outcomes that matter for patients. To this end, analytical methodologies to identify high risk multimorbidity patient groups, as well as to evaluate and define evidence-based clinical pathways associated with each patient group will be used. The project contributes to improved healthcare delivery through precision and personalized medicine and to contribute to market sustainability using new technologies. INESC-ID leads a project activity for identifying and and characterizing the main clusters of multimorbidity in clinical data. The applicant to be hired will join a team engaged in performing exploratory analysis of clinical data for clinical phenotyping and identification of most frequent representative groups iin multimorbidity, and investigation and exploration of different data mining algorithms supporting this task.

Specific Requirements

The candidates should have an MSc in Computer Engineering, Biomedical Engineering or equivalent scientific areas.

 

 

 

By the grant start date, the candidate must be enrolled in

  1. a PhD programme – art. 6º, n.1

    (https://www.fct.pt/apoios/bolsas/docs/RegulamentoBolsasFCT2019.pdf)

or

  1. a non-degree programme – art. 6º, n. 2

    (https://www.fct.pt/apoios/bolsas/docs/RegulamentoBolsasFCT2019.pdf )

Map Information

Job Work Location Personal Assistance locations
Work location(s)
1 position(s) available at
INESC ID
Portugal
Lisboa
Lisboa
1000-029
Rua Alves Redol, 9

EURAXESS offer ID: 681190

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