02/03/2020
Logo of Marie Skłodowska-Curie Actions

2 PhD scholarships in the area of Bias in Artificial Intelligence at University of Pisa

This job offer has expired


  • ORGANISATION/COMPANY
    University of Pisa
  • RESEARCH FIELD
    Computer science
  • RESEARCHER PROFILE
    First Stage Researcher (R1)
  • APPLICATION DEADLINE
    02/06/2020 17:00 - Europe/Brussels
  • LOCATION
    Italy › Pisa
  • TYPE OF CONTRACT
    Temporary
  • JOB STATUS
    Full-time
  • HOURS PER WEEK
    40
  • OFFER STARTING DATE
    01/09/2020
  • EU RESEARCH FRAMEWORK PROGRAMME
    H2020 / Marie Skłodowska-Curie Actions
  • MARIE CURIE GRANT AGREEMENT NUMBER
    860630

OFFER DESCRIPTION

Call for applications: 2 Marie Skłodowska-Curie Early Stage Researchers

Fully funded PhD positions for 3 years.

Closing date (extended): June 2nd 2020

Interview period: June 2020

Positions starts: September 1st, 2020 (indicative)

H2020 MSCA Project: NoBIAS ITN, Grant Agreement No. 860630

PhD position UNIPI-1: "Causality analysis of data for domain-specific bias understanding"

PhD position UNIPI-2: "Declarative explanation of black-box decisions"

The Department of Computer Science at the University of Pisa (UNIPI) has two open PhD positions in the area of Bias in Artificial Intelligence. Within the department, the research group KDD Lab (Knowledge Discovery and Data Mining) is actively involved in the area of Ethical Artificial Intelligence with pioneering contributions on discrimination discovery, fairness in ML, explainable AI, privacy, and segregation discovery. 

The NoBIAS project

The 2 PhD positions are part of NoBIAS - Artificial Intelligence without Bias, a project funded by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie - Innovative Training Networks (ITN), Grant Agreement No. 860630. NoBIAS aims at developing novel methods for AI-based decision making without bias by taking into account ethical and legal considerations in the design of technical solutions. The core objectives of NoBIAS are to understand legal, social and technical challenges of bias in AI-decision making, to counter them by developing fairness-aware algorithms, to automatically explain AI results, and to document the overall process for data provenance and transparency. NoBIAS will train a cohort of 15 ESRs (Early-Stage Researchers) to address problems with bias through multi-disciplinary training and research in computer science, machine learning, artificial intelligence, law and social science.

How you will work

ESRs of the NoBIAS project will acquire practical expertise in a variety of sectors from healthcare, telecommunication, finance, marketing, media, software, and legal consultancy to broadly foster legal compliance and innovation. Technical, interdisciplinary and soft-skills will give ESRs a head start towards future leadership in industry, academia, or government. Each ESR will work in an individual research project in a different host institution and will participate in academic and inter-sectoral secondments at the premises of other NoBIAS members. The positions are offered full-time for three years (36 months). As a successful candidate, you will:

  • Conduct research at the Department of Computer Science of the University of Pisa in the context of the NoBIAS project.
  • Engage in the NoBIAS research activities and actively collaborate within the consortium.
  • Actively participate in the training programme offered by the NoBIAS ITN.
  • Engage with researchers at NoBIAS partner organizations across the EU.
  • Conduct research visits and secondments according to the individual career development plan.

Your tasks for UNIPI-1 position: "Causality analysis of data for domain-specific bias understanding"

Motivation & Objectives: The ability to learn causality is a significant component of human-level intelligence which is hard to replicate in AI. This PhD thesis addresses the discovery and understanding of causal influences among variables. Approaches will be designed for learning such influences from the data or, for a given domain, both from data and domain knowledge. They will advance state-of-the-art in data sanitization, fair decision making, and explainability of AI. Secondments will provide grounds on the representational models of expert knowledge and for experimentation/validation in the application scenarios of insurance and credit.

Expected results: Methods for general and domain specific causal analysis for bias quantification, understanding, and mitigation in data.

Your tasks for UNIPI-2 position: "Declarative explanation of black-box decisions"

Motivation & Objectives: The rise of sophisticated ML has brought accurate but obscure decision systems, thus undermining transparency, trust, and the adoption of AI in socially sensitive and safety-critical contexts. This PhD thesis will investigate declarative approaches, based on formal logic rules, for explaining ML black boxes decisions, including operators for composing and abstracting rules into a higher level of understanding. Secondments will provide grounds on the legal acquis and validation in challenging industrial application scenarios.

Expected results: Theory and methodology of explanation, i.e., a comprehensive logical/statistical framework of data-driven discovery of explanatory rules providing understandable, solid and succinct explanations of salient properties of black boxes.

 

More Information

Benefits

The selected candidate will be appointed a temporary contract for 36 months, salary will be in line with the funding schemes of MSCA action, and in accordance with Italian rules and regulations, as stated in the Grant Agreement and MSCA Guide for Applicants. Monthly salary (living allowance + mobility allowance) will be of approx. 4.000€ (gross amount subject to health insurance/tax deductions), allocated following Italian specific contract conditions for MSCA candidates. Additional family allowance will be granted upon specific conditions.

Eligibility criteria

To be eligible, the applicant must satisfy the mobility requirements of Marie Skłodowska-Curie actions. At the time of recruitment, the potential candidate:

  • "must not have resided or carried out their main activity (work, studies, etc.) in the country of the recruiting beneficiary for more than 12 months in the 3 years immediately before the recruitment date. Compulsory national service, short stays such as holidays, and time spent as part of a procedure for obtaining refugee status under the Geneva Convention are not taken into account"
  • and "be in the first four years (full-time equivalent research experience) of their research careers and have not been awarded a doctoral degree".

We welcome all applicants, and specifically encourage people from traditionally under-represented groups to apply.

Applications that do not meet the eligibility criteria or that are received after the deadline will not be considered.

 

Required documents

  • Detailed CV in Europass format (template available in the following link) in English, highlighting your achievements and fit to the applied position.
  • Scanned copies of BSc and MSc transcripts, with certified translation in English (if the degree qualification is not in English or in Italian);
  • A motivation letter in English, highlighting why you will be a good fit for the position and why you want to be a NoBIAS ESR to carry out of a PhD.
  • Contact details or recommendation letters of two referees in English or in certified translation;
  • Scanned copy of valid identification document and, if applicable, of the Italian fiscal code;
  • Proof of excellent command of English (e.g., IELTS, TOEFL, Cambridge or equivalent). This is not required in case of native English speakers (i.e., English is your mother tongue);
  • A copy of the applicant's scientific publications relevant for this selection;
  • The list of scientific publications and skill qualifications of the applicant, dated and signed.

 

Application procedure

All required documents should not exceed 100 megabyte in total and are to be submitted in PDF format only, using the application form at the following link: http://nobias.di.unipi.it/apply.

Selection process

Applications will be processed according to the rules of the University of Pisa and in compliance with the general rules for projects in the H2020/Marie Skłodowska-Curie programmes.

For the selection procedure, the NoBIAS consortium has appointed a Committee, consisting of five members:

  • Professor Bettina Berendt, Katholieke Universiteit Leuven
  • Dr. Klaus Broelemann, SCHUFA Holding AG
  • Professor Salvatore Ruggieri, University of Pisa
  • Professor Sophie Stalla-Bourdillon, University of Southampton
  • Professor Franco Turini, University of Pisa

The selection is assessed by qualifications and an interview.

The total rating allowed is 100/100. Qualifications and publications will be assigned up to 60 points, with a minimum passing rate of 36/60. The interview will be assigned up to 40 points, with a minimum passing rate of 24/40. The final ranking list will be compiled considering both ratings. There will be a separate ranking list for UNIPI-1 and UNIPI-2 positions.

 

The interview, reserved only to applicants passing the qualification rate, will be held at the University of Pisa, Department of Computer Science, Largo B. Pontecorvo 3, Pisa, Italy. Candidates unable to attend the interview at the University of Pisa will be allowed to be interviewed via web or conference call. The Selection committee is appointed to establish the duly examination of the candidates and shall acquire each candidate’s copy of an identity card or passport.

 

Approval and Enrollment in the PhD programme

The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in one of the general PhD programmes at the Department of Computer Science of University of Pisa. 

Additional comments

About the University of Pisa

The University of Pisa, officially established in 1343, is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by respect and academic freedom tempered by responsibility. Find useful information on the University of Pisa and on history, culture, traditions and nature of Pisa, Tuscany and Italy at the student guide. Additional information at the welcome office website.

 

Further information

Further information may be obtained from Prof. Salvatore Ruggieri, (+39) 050 2212782 or salvatore.ruggieri@unipi.it

You can read more about Department of Computer Science at http://www.di.unipi.it/ and about the KDD Lab at https://kdd.isti.cnr.it/.

Offer Requirements

  • REQUIRED LANGUAGES
    ENGLISH: Excellent

Skills/Qualifications

Candidates should have a two-year Master's degree (120 ECTS points)  or equivalent degree (see EQF level 7) .Candidates may apply prior to obtaining their Master's degree but cannot begin before having received it. Their academic record is excellent. 

Candidates care not only about AI, but also about the ethical dimension of computing systems, and they are motivated to learning and taking a critical and interdisciplinary approach that values the social sciences and humanities. Prior experience with topics with an ethical dimension is a plus (privacy/data protection, fairness/non-discrimination, explainability, bias and misinformation, etc.).

Candidates work efficiently and reliably, independently as well as in teams. They have very good communication skills and scientific curiosity. They are fluent in at least one programming language. Their English is excellent. Candidates are flexible and prepared to travel and to integrate into the local teams, while keeping a focus on your PhD and on delivering scientific and other project-related output.

Work location(s)
2 position(s) available at
Department of Computer Science, University of Pisa
Italy
PI
Pisa
56127
Largo B. Pontecorvo 3

EURAXESS offer ID: 499632

Disclaimer:

The responsibility for the jobs published on this website, including the job description, lies entirely with the publishing institutions. The application is handled uniquely by the employer, who is also fully responsible for the recruitment and selection processes.

 

Please contact support@euraxess.org if you wish to download all jobs in XML.