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EURAXESS

1 | RESEARCH GRANT TYPE ONE research grant for candidates with Master degree with reference number BI| BI|2023/361 is now available under the scope of project Center for Responsible AI, funded by RRP

INESC ID
13/01/2023

Job Information

Organisation/Company
INESC ID
Research Field
Engineering » Computer engineering
Engineering
Researcher Profile
First Stage Researcher (R1)
Country
Portugal
Application Deadline
Type of Contract
Other
Job Status
Other
Is the job funded through the EU Research Framework Programme?
Not funded by an EU programme
Reference Number
C. for Responsible AI-Refª C645008882-00000055-BI|2023/361
Is the Job related to staff position within a Research Infrastructure?
No

Offer Description

Public notice for research grant

Center for Responsible AI

Refª C645008882-00000055

BI|2023/361

 

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

ONEresearch grant for candidates with Master degree  with reference numberBI|2023/361 is now available under the scope of project Center for Responsible AI, funded byRecovery and Resilience Plan (RRP) and under the following conditions:

2 | DURATION

12 months, starting in March 2023

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

https://files.dre.pt/2s/2019/12/241000000/0009100105.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)

 

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

https://files.dre.pt/2s/2019/12/241000000/0009100105.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/

  1. Recovery and Resilience Plan (RRP)

https://recuperarportugal.gov.pt/

 

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 1144,64is in accordance with the values stipulated in the “Regulations for Research Grants of the Foundation for Science and Technology” in force https://former.fct.pt/apoios/bolsas/docs/Tabela_de_Valores_SMM_2022.pdf and shall be rendered through a monthly bank transfer to an account held by the grantee.

5 | OBJECTIVES/WORKPLAN

State-of-the-art AI models are unsustainably hunger for data and computational resources: the recent GPT-3 model developed by OpenAI has 175 billion parameters, was trained on 500 billion words, and took 3.14E23 flops to train (on a domestic GPU, it would cost $4.6M and it would require 355 years to train such a model). This has a daunting carbon footprint and poses serious environmental concerns. Recent literature has shown that the training of a state of the art ML model for NLP can emit 5x more CO2 than a car during its entire lifespan.

The assignee of this research grant will investigate and develop new scientific methods and technologies for making AI systems more energy and data efficient -- an important goal for Data4Green and the European Green Deal.

More in detail, the focus of this grant will be on investigating the adoption of emerging hardware mechanisms (In-memory processing devices, Non-Volatile RAM, Transactional Memory) to increase efficiency of storage and intra-node synchronization.

6 | SCIENTIFIC SUPERVISION

The activity will be supervised by Paolo Romano, Associate Professor at Instituto Superior Técnico and Researcher at INESC-ID.

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

7 | ADMISSION REQUIREMENTS

The candidates should have MSc degree in Computer Engineering or Computer Science, or related areas.

 

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

  1. a PhD programme – art. 6º, n.1

https://files.dre.pt/2s/2019/12/241000000/0009100105.pdf

or

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

https://files.dre.pt/2s/2019/12/241000000/0009100105.pdf

 

Preferential factors:

Preference will be given to candidates who have:

  • Experience with the development and benchmarking of Transactional Memory systems (TinySTM, NORec, HTM)
  • Experience with In-Memory Processing Devices
  • Experience with developing AI/ML models and Python programming
  • Experience with low-level hardware programming
  • Fluency in English (Written and Spoken)

8 | EVALUATION CRITERIA AND COMMITEE

The selection will be according to the following criteria:

  1. Experience with the development and benchmarking of Transactional Memory systems (TinySTM, NORec, HTM)- 25%
  2. Experience with In-Memory Processing Devices - 25%
  3. Experience with low-level hardware programming - 15%
  4. Experience with developing AI/ML models and Python programming - 10%
  5. Fluency in English (Written and Spoken) - 25%

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

 

Jury

Name

Professional Status

Institutions

President

Paolo Romano

Researcher / Associate Professor

INESC ID | Tecnico

Member

Luís Eduardo Teixeira Rodrigues

Researcher / Full Professor

INESC ID | Tecnico

Member

Nuno Miguel Carvalho Santos

Researcher / Associate Professor

INESC ID | Tecnico

Substitute member

João Pedro Faria Mendonça Barreto

Researcher / Assistant Professor

INESC ID | Tecnico

Substitute member

Miguel Ângelo Marques de Matos

Researcher / Assistant Professor

INESC ID | Tecnico

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.

 

 

 

 

 

 

10.1

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 the copy of 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 copy of 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:

 

 

https://www.dges.gov.pt/en/pagina/degree-and-diploma-recognition

 

 

10.2

Detailed list of grades (pdf form);

 

 

 

 

10.3

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

 

 

 

In the application submission, the candidates may replace the proof of enrolment 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)

 

 

 

10.4

Detailed curriculum vitae (pdf form);

 

 

 

 

10.5

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

 

 

 

 

     

11 | Application Dates

From

 

To

16-01-2023

 

31-01-2023

 

 

Requirements

Research Field
Engineering » Computer engineering
Education Level
Master Degree or equivalent
Skills/Qualifications

State-of-the-art AI models are unsustainably hunger for data and computational resources: the recent GPT-3 model developed by OpenAI has 175 billion parameters, was trained on 500 billion words, and took 3.14E23 flops to train (on a domestic GPU, it would cost $4.6M and it would require 355 years to train such a model). This has a daunting carbon footprint and poses serious environmental concerns. Recent literature has shown that the training of a state of the art ML model for NLP can emit 5x more CO2 than a car during its entire lifespan.

The assignee of this research grant will investigate and develop new scientific methods and technologies for making AI systems more energy and data efficient -- an important goal for Data4Green and the European Green Deal.

More in detail, the focus of this grant will be on investigating the adoption of emerging hardware mechanisms (In-memory processing devices, Non-Volatile RAM, Transactional Memory) to increase efficiency of storage and intra-node synchronization.

Specific Requirements

The candidates should have MSc degree in Computer Engineering or Computer Science, or related areas.

 

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

  1. a PhD programme – art. 6º, n.1

https://files.dre.pt/2s/2019/12/241000000/0009100105.pdf

or

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

https://files.dre.pt/2s/2019/12/241000000/0009100105.pdf

Languages
ENGLISH
Level
Good

Additional Information

Benefits

The monthly amount of the grant 1144,64is in accordance with the values stipulated in the “Regulations for Research Grants of the Foundation for Science and Technology” in force https://former.fct.pt/apoios/bolsas/docs/Tabela_de_Valores_SMM_2022.pdf and shall be rendered through a monthly bank transfer to an account held by the grantee.

Eligibility criteria

The candidates should have MSc degree in Computer Engineering or Computer Science, or related areas.

 

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

  1. a PhD programme – art. 6º, n.1

https://files.dre.pt/2s/2019/12/241000000/0009100105.pdf

or

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

https://files.dre.pt/2s/2019/12/241000000/0009100105.pdf

Selection process

The selection will be according to the following criteria:

  1. Experience with the development and benchmarking of Transactional Memory systems (TinySTM, NORec, HTM)- 25%
  2. Experience with In-Memory Processing Devices - 25%
  3. Experience with low-level hardware programming - 15%
  4. Experience with developing AI/ML models and Python programming - 10%
  5. Fluency in English (Written and Spoken) - 25%

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

Additional comments

Preference will be given to candidates who have:

  • Experience with the development and benchmarking of Transactional Memory systems (TinySTM, NORec, HTM)
  • Experience with In-Memory Processing Devices
  • Experience with developing AI/ML models and Python programming
  • Experience with low-level hardware programming
  • Fluency in English (Written and Spoken)

Work Location(s)

Number of offers available
1
Company/Institute
INESC-ID
Country
Portugal
State/Province
Lisbon
City
Lisbon
Postal Code
1000-029
Street
Rua Alves Redol, 9
Geofield

Where to apply

E-mail
rh@inesc-id.pt

Contact

State/Province
Lisboa
City
Lisboa
Street
Rua Alves Redol, 9
Postal Code
1000-029
E-Mail
rh@inesc-id.pt