Research Engineer AI Models Evaluation and Validation @ OpenEBench (RE3) – AI4S
Job Description
The Barcelona Supercomputing Center – Centro Nacional de Supercomputación (BSC-CNS) is the leading supercomputing center in Spain. It houses MareNostrum, one of the most powerful supercomputers in Europe, was a founding and hosting member of the former European HPC infrastructure PRACE (Partnership for Advanced Computing in Europe), and is now hosting entity for EuroHPC JU, the Joint Undertaking that leads large-scale investments and HPC provision in Europe. The mission of BSC is to research, develop and manage information technologies in order to facilitate scientific progress. BSC combines HPC service provision and R&D into both computer and computational science (life, earth and engineering sciences) under one roof, and currently has over 1000 staff from 60 countries.
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We are particularly interested for this role in the strengths and lived experiences of women and underrepresented groups to help us avoid perpetuating biases and oversights in science and IT research. In instances of equal merit, the incorporation of the under-represented sex will be favoured.
We promote Equity, Diversity and Inclusion, fostering an environment where each and every one of us is appreciated for who we are, regardless of our differences.
If you consider that you do not meet all the requirements, we encourage you to continue applying for the job offer. We value diversity of experiences and skills, and you could bring unique perspectives to our team.
Context And Mission
The Spanish National Bioinformatics Institute (INB) was created in 2003 with the mission to support bioinformatics activities across the country. Since then, it has evolved to keep up with emerging needs – especially in the field of creating, maintaining and extending technological infrastructures that facilitate research activities in the broad domain of Life Sciences. Since 2017, the INB is the Spanish Node of ELIXIR (ELIXIR-ES), the pan-European Research Infrastructure for the management of research data and other digital assets in Life Sciences across 22 national members and 3 observers (https://elixir-europe.org/).
Both the INB Technical Coordination Hub and the INB Computational Node, part of the Life Sciences Department at the Barcelona Supercomputing Center (BSC-CNS), participate and lead different local, national and international – mainly European – projects relate to research data and software management as well as to the set-up of virtual research environments where data and software can be utilised.
As part of the EU-funded ELIXIR-EXCELERATE project, both teams started the development of OpenEBench (https://openebench.bsc.es), the ELIXIR open data platform to support both the technical monitoring of research software – including workflows – and the scientific benchmarking activities led by research communities. Since its inception, OpenEBench has growth to monitor more than 43,000 individual research software entries and support more than 16 different research communities at different maturation stages, including the participation of different funded projects like EUCanImage, EUCAIM, DataTools4Heart, VEIS among others.
Artificial Intelligence (AI) as a field has experienced an accelerated growth over the past years with many applications having a great impact on the general population, including the use of AI/ML models to support decision-making processes in clinical applications. However, limited efforts have been put to understand and validate AI/ML models in terms of both the data and software used to train and refine them. Thus, the INB teams are seeking for a research software engineer to develop methodologies for carrying such systematic evaluation and validation efforts in the context of OpenEBench and connected with ongoing projects, e.g. EUCAIM, and others to come. The objective is to develop strategies and methodologies that can be utilised by the different research communities working with OpenEBench to understand the potential biases present in the input data and limitations of the generated AI/ML models. Such a generalization should contribute to foster broader discussions among the different communities leading to the iterative refinement process of it.
The funding for these actions/fellowships and contracts comes from the European Union Recovery and Resilience Facility – Next Generation, within the framework of the General Invitation by the public business entity Red.es to participate in the talent attraction and retention programs within Investment 4 of Component 19 of the Recovery, Transformation, and Resilience Plan.
For more information, please check: https://www.bsc.es/join-us/excellence-career-opportunities/ai4s
“La financiación de estas actuaciones/becas y contratos, procede del Mecanismo de Recuperación y Resiliencia de la Unión Europea-Next Generation, en el marco de la Invitación General de la entidad pública empresarial Red.es para participar en los programas de atracción y retención del talento dentro de la Inversión 4 del Componente 19 del Plan de Recuperación, Transformación y Resiliencia.
Para más información: https://www.bsc.es/join-us/excellence-career-opportunities/ai4s “
Key Duties
- Landscape the current efforts on AI/ML models evaluation and validation in Life Sciences and work towards the integration into the exciting fora.
- Lead the development of strategies and a generalizable methodology for AI/ML models evaluation and validation in close collaboration with various research communities and relevant projects.
- Drive the adoption of such methodology in the context of OpenEBench preparing the necessary extensions of the platforms.
- Ensure the timely dissemination of results – including partial ones – across the various existing channels at institutional, local, national and international levels.
Requirements
- Education
- Superior degree in bioinformatics-related or data science related fields.
- Essential Knowledge and Professional Experience
- At least, three (3) years of experience on managing research data used in the context of AI/ML models generation, including the detection of potential biases.
- At least, three (3) years of experience on AI/ML models generation, evaluation and validation.
- At least, three (3) years of experience as research software engineer developing high-quality software that is sustainable, is well documented and follows community-led development good practices.
- Additional Knowledge and Professional Experience
- Experience on applying the FAIR principles to data, software, workflows and/or AI/ML models.
- Experience on developing FAIR-by-design data models to ensure the long-term sustainability of relevant metadata.
- Fluency in English is essential. Proficiency in Spanish and other European languages would be advantageous.
- Competences
- Ability to understand scientific literature, and software documentation.
- Ability to communicate scientific results.
- Ability to work independently, in a team and in a multi-cultural environment.
- Ability to represent the team in international project meetings and research community.
- Ability to mentor and contribute towards the professional development of junior team members.
Conditions
- The position will be located at BSC within the Life Sciences Department
- We offer a full-time contract (37.5h/week), a good working environment, a highly stimulating environment with state-of-the-art infrastructure, flexible working hours, extensive training plan, restaurant tickets, private health insurance
- Duration: 4 years
- Holidays: 23 paid vacation days plus 24th and 31st of December per our collective agreement
- Salary: 50.000,00€
- Additional Expenses Grant: Each fellowship will be associated with a grant for additional expenses, such as IT equipment, travel, training, stays, etc.
- Starting date: asap – the incorporation for this vacancy must be before the 16th of December 2024
Applications procedure and process
All applications must be submitted via the BSC website and contain:
- A full CV in English, including contact details.
- A cover/motivation letter with a statement of interest in English, clearly specifying for which specific area and topics the applicant wishes to be considered. Additionally, two references for further contacts must be included. Applications without this document will not be considered.
Development of the recruitment process
The selection will be carried out through a competitive examination system (“Concurso-Oposición”). The recruitment process consists of two phases:
- Curriculum Analysis: Evaluation of previous experience and/or scientific history, degree, training, and other professional information relevant to the position. – 40 points
- Interview phase: The highest-rated candidates at the curriculum level will be invited to the interview phase, conducted by the corresponding department and Human Resources. In this phase, technical competencies, knowledge, skills, and professional experience related to the position, as well as the required personal competencies, will be evaluated. – 60 points. A minimum of 30 points out of 60 must be obtained to be eligible for the position.
The recruitment panel will be composed of at least three people, ensuring at least 25% representation of women.
In accordance with OTM-R principles, a gender-balanced recruitment panel is formed for each vacancy at the beginning of the process. After reviewing the content of the applications, the panel will begin the interviews, with at least one technical and one administrative interview. At a minimum, a personality questionnaire as well as a technical exercise will be conducted during the process.
The panel will make a final decision, and all individuals who participated in the interview phase will receive feedback with details on the acceptance or rejection of their profile.