El BSC AI4Science Fellowships (AI4S) es un programa de atracción y retención de talento que tiene como objetivo la convergencia de HPC e IA, así como la creación y consolidación de líneas de investigación en los departamentos del BSC-CNS (Computer Sciences, Life Sciences, Earth Sciences, Computer Applications in Science and Engineering - CASE), aprovechando las capacidades computacionales del MareNostrum 5.
Esta iniciativa es parte de los programas de atracción y retención del talento dentro de la inversión 4 del componente 19 del Plan de Recuperación, Transformación y Resiliencia, C005/24-ED CV1.
Descripción
El AI4S busca afianzar las líneas de investigación existentes (Departamentos de CS, LS, ES, Y CASE), e impulsar el Instituto IA, tal como se ha descrito en los objetivos del Programa. Para ello, el BSC espera atraer o retener 158 personas becadas que estarán contratadas a jornada completa, los 4 años que dura el programa.
- Remuneración: La remuneración se establecerá de acuerdo con las tablas salariales del programa y se especificará en cada vacante publicada de forma transparente.
- Dotación de bolsa de gastos adicionales: Cada beca tendrá asociada una bolsa para gastos adicionales, como equipamiento IT, viajes, formación, estancias, etc.
- Jornada laboral: Jornada completa (37.5h semanales). No se considerarán las posiciones part-time.
- Contrato: 4 años.
- Incorporación: Debido a las características del BSC AI 4 Science Fellowships (AI4S), todas las personas que superen con éxito el proceso de selección deberán ser incorporadas antes del 31/12/2024.
Vacantes AI4S
Vacantes abiertas:
Computer Sciences:
- Research Engineer - AI4S - LLMs for Code Parallelization (RE3-T2)
- Researcher - AI-based Edge-to-Cloud computing continuum solutions - AI4S (R2)
- PhD on Programming model for edge to cloud through swarm methodologies - AI4S (R1)
- Synthetic data for DL - AI4S (R2)
- RTL HW for AI - AI4S (RE1)
- Synthetic data for DL - AI4S (RE2)
- Synthetic data for DL - AI4S (RE2)
- LLVM Software Engineer (RE2)
- LLVM Software Engineer (RE2)
- Research Engineer - AI4S - Foundational models for Chip Design (RE2)
- Vector and matrix accelerators for AI workloads - AI4S - (RE1)
- HPC Performance Engineer for AI frameworks - AI4S (RE1)
- HPC Performance Engineer - AI4S (RE1)
- HPC analyst, researcher, and software developer - AI4S (R3)
- Research Engineer - Foundational Models - AI4S (RE2)
- Research Engineer - Foundational Models - AI4S (RE2)
- Researcher - Multimodal foundational models and XAI - AI4S (R2)
- Research Engineer on AI HW/SW for Edge AI systems - AI4S (RE3)
- Artificial Intelligence driven solutions for accelerators and communications - AI4S (RE1)
Life Sciences:
- Postdoctoral Researcher - AI/ML in specific research lines in Life Sciences (R2) - AI4S
- Postdoctoral Researcher - AI/ML in specific research lines in Life Sciences (R2) - AI4S
- Postdoctoral Researcher - AI/ML in specific research lines in Life Sciences (R2) - AI4S
- Postdoctoral Researcher - AI/ML in specific research lines in Life Sciences (R3) - AI4S
- Postdoctoral Researcher - AI/ML in specific research lines in Life Sciences (R3) - AI4S
- Postdoctoral Researcher - AI/ML in specific research lines in Life Sciences (R3) - AI4S
- Postdoctoral Researcher - AI/ML in specific research lines in Life Sciences (R3) - AI4S
- Postdoctoral Researcher - AI/ML in specific research lines in Life Sciences (R3) - AI4S
- Postdoctoral Researcher AI and integrative methods for comparative genomics and metagenomics (R2) - AI4S
- Group leader Social Link Analytics unit - biases and evaluation of AI tools in health / disinformation in social networks / Bioinfo4Women (R4) - AI4S
- Established Researcher Data science and AI expert for Clinical NLP and Language Models (R3) - AI4S
- Recognised Researcher ML methods for histopathology image analysis in human development (R2) - AI4S
- Postdoctoral Researcher LLMs Genomics (R2) - AI4S
- Post-doc in AI for Biomedical Multi-Omic Data Analysis for Cancer Precision Medicine (R2) - AI4S
- Research Engineer AI Models Evaluation and Validation @ OpenEBench (RE3) - AI4S
- Research Engineer Securing Processing Environments for Analysing Sensitive Data (RE3) - AI4S
- Postdoctoral Researcher Evaluation of AI systems and applications in health (R3) - AI4S
- Postdoctoral Researcher Developing novel AI workflows to uncover tissue architectural changes in human aging (R2) - AI4S
- Postdoctoral Researcher Applying Deep learning to Healthcare (R2) - AI4S
- Research Engineer Clinical LLMs (RE2) - AI4S
Earth Sciences:
- Researcher - Exploitation of next-generation Earth System observation missions (R3) - AI4S
- Researcher - Understanding air pollution patterns, trends and impacts (R3) - AI4S
- Researcher - Advancing atmospheric emission estimation (R3) - AI4S
- Researcher - Enhancing atmospheric chemistry modeling capabilities with machine learning and other cutting-edge technologies (R3) - AI4S
- Researcher - Modelling Tools for Climate and Health (R2) -AI4S
- Research Engineer - Data Science for Climate and Health (RE2) - AI4S
- Researcher - Using AI to improve climate predictions, by optimised ensemble selection and process-based calibration (R3) - AI4S
- Researcher - Weather dynamics and their effect on climate extremes in Digital Twins of the Earth and high-resolution observations (R3) - AI4S
- Researcher - Enabling carbon cycle and improving land surface representation and land-atmosphere interactions in Digital Twins of the Earth System through data-driven solutions (R2) - AI4S
- Postdoctoral Researcher in Artificial Intelligence Applied to Climate Services (R2) - AI4S
- Postdoctoral Researcher in Artificial Intelligence Applied to Climate Services (R2) - AI4S
- Postdoctoral Researcher - Integrated Urban Air Quality Modeling: Bridging Physics and Data Science (R2)
- Research Engineer - AI-Driven Development of ML-Based Climate Forecast Models (RE3) - AI4S
- Researcher - Earth system services and AI (R3) - AI4S
- Research - Earth observation products (R3)
CASE - Computer Applications in Science & Engineering:
Director's office:
- esearcher in computational politcal communication (R2) - AI4S
- Education & Training Officer - AI Factory Training Program Coordinator - AI4S
- Education & Training Officer - Doctoral Program Coordinator - AI4S
- Data scientist for Computational Social Sciences and Humanities (RE2) - AI4S
- Sustainability and Climate Market and Business Analyst - AI4S
Operations:
- EuroCC-Spain-RES Project Officer - AI4S
- AI Support Engineer - High-Performance Computing (HPC) Projects - AI4S
- AI Application Support Engineer - High-Performance Computing (HPC) projects - AI4S
- HPC/AI Systems Engineer - AI4S
- HPC/AI Systems Engineer - AI4S
- AI Application Support Specialist - AI4S
- AI Application Support Specialist for High-Scalability Projects - AI4S
- AI Senior Application Support Specialist - AI4S
Vacantes cerradas:
Computer Sciences:
- Research Engineer - AI4S - LLMs for Code Parallelization (RE2)
- Research Engineer - AI4S - LLMs for Chip Design (RE1)
- Research Engineer - Foundational Models - AI4S (RE2)
- Research Engineer - AI4S - LLMs for Chip Design (RE2)
- Research Engineer on Diverse Redundancy for AI - AI4S (RE3)
- PostDoc on AI modelization for Edge AI systems - AI4S (R3)
- Postdoc on Parallel Machine Learning - AI4S (R2)
- Researcher - HPC memory systems (R2) - AI4S
- Research Engineer – Agent-based models for explainability – AI4S (RE2)
- Research Engineer – Agent-based models for transfer learning – AI4S (RE2)
- Vector and matrix accelerators for AI workloads - AI4S (RE2)
- Arithmetic units and data representation for AI - AI4S (RE1)
- Analog and inmemory computation for AI - AI4S (RE3)
- Research Engineer on Emulation and Evaluation of Novel Architectures for AI - AI4S(RE1)
- Research Engineer on Emulation and Evaluation of Novel Architectures for AI - AI4S(RE1)
- Researcher on Computer Architecture for AI - AI 4S(R2)
- Research Engineer – AI4S (RE2)
- Research Engineer – AI4S (RE2)
- Senior RTL HW for AI - AI4S (R2)
Life Sciences:
- Team Leader Speech, Language Technologies (RE3_T1) - AI4S
- Engineering Manager Speech and Speaker Technologies (RE3) - AI4S
- Large Language Models for Multimodal Synthetic Data Generation and Evaluation in Biomedicine (R2) - AI4S
- Engineering Manager Speech, Language Technologies (RE3) - AI4S
- Post-doc in AI for Biomedical Multi-Omic Data Analysis for Cancer Precision Medicine (R3) - AI4S
- Postdoctoral Researcher human digital twins (R3) - AI4S
- Postdoctoral Researcher Language models for bioprostecting and engineering (R3) - AI4S
- MLOps senior researcher in Language Technologies (RE3_T1) - AI4S
- Research Engineer Model training, new architectures, performance enhancements, generative AI evaluation (RE2) - AI4S
- Senior research engineer Generative Artificial Intelligence for Biomedical Research (RE3) - AI4S
Earth Sciences:
CASE - Computer Applications in Science & Engineering:
- PhD student for the Fusion Group - AI4S (R1)
- Researcher - Turbulence modelling via ML (R2) - AI4S
- Established Researcher in earthquake hazard assessment with HPC and AI (R3) - AI4S
- Senior researcher in computational materials modelling (R3) - AI4S
- PhD in machine learning models for rapid earthquake hazard assessment (R1) - AI4S
- Senior Researcher on Computational Modeling for Fusion (R3) - AI4S
- Researcher - AI social urban digital twins (R3) - AI4S
- Researcher - AI applied to sports and live entertainment industry (RE3_T1) - AI4S
- Researcher - Digital Ethics for Dual-Use Technologies (R3) - AI4S
- Researcher in computational materials science (R2) - AI4S
- Researcher in high-order methods (R2) - AI4S
- Researcher - High-fidelty hypersonic flows (R3) - AI4S
- Researcher on Development of advanced methods for hydrogen combustion using ML-based algorithms (R3)
- Postdoctoral Researcher- AI/ML-assisted analysis of spray flame combustion for aviation fuels (R2)
- Researcher Development of soot models using Machine Learning algorithms (R2) - AI4S
- Researcher - Development of multi-regime and dual-fuel models with Artificial Intelligence for gas turbine combustion applications (R2) – AI4S
- Postdoc Researcher - Quantum Computation (R2)
- Postdoc Researcher - Quantum Computation (R2)
- Research Engineer for HPC and AI for critical infrastructure resilience (RE3) - AI4S
- Researcher - Solid Mechanics researcher (R3) - AI4S
- PHD Student - HPC and ML in Electromagnetic modelling (R1) - AI4S
- Researcher - Adaptive mesh refinement techinques exploting DRL (R3) - AI4S
- Research engineer - Optimizing Bacteriophage Therapy in the Respiratory System via HPC (RE2) - AI4S
- Researcher - Virtual Lung Dosimetry for Health Outcomes (R3) - AI4S
- Researcher - Adaptive mesh refinement for wind farm simulation (RE3_T1) - AI4S
- Researcher in geometry and meshing for simulation (R3) - AI4S
Director's office:
- Computational Social and Data Scientist (RE2) - AI4S
- Lead of Museums and Cultural Heritage Technologies and Strategy (RE3_T2) - AI4S
- Strategic Initiatives Coordinator - AI4S
- AI Market and Business Analyst - AI4S
- Lead of the Data and Methods for HPCSSH (RE3_T2) - AI4S
- Senior Research Engineer Data Strategist, Science for Policy (RE3-T1) - AI4S
- Researcher in Digital Humanities and Computational Linguistics (R3) - AI4S
- Data Researcher and Engineer (RE3) - AI4S
- AI Market and Business Analyst - AI4S
- Postdoctoral Researcher in Labor Market (R2) - AI4S
Desarrollo del proceso de selección
Todas las candidaturas deberán ser presentadas a través de la página web del BSC y contener:
- Un CV completo en inglés, incluyendo detalles de contacto.
- Una carta de presentación/motivación con una declaración de interés en inglés, especificando claramente para qué área y temas específicos desea ser considerada la persona aplicante. También se deberá incluir dos contactos para referencias adicionales. Las solicitudes sin este documento no serán consideradas.
La selección se llevará a cabo a través del sistema de concurso-oposición. El proceso de selección cuenta con dos fases:
- Análisis del currículum: evaluación de la experiencia previa y/o historial científico, título, formación y otra información profesional relevante para el puesto. - 40 puntos
- Fase de entrevistas: Las candidaturas mejor valoradas a nivel curricular serán invitadas a la fase de entrevistas, conducidas por el departamento correspondiente y por Recursos Humanos. En esta fase se evaluarán las competencias técnicas, conocimientos, habilidades y experiencia profesional vinculadas al puesto, así como las competencias personales requeridas. - 60 puntos. Se deberá obtener un mínimo de 30 puntos del total de 60 puntos para ser elegible para la posición.
Cada proceso de selección cuenta con un panel de selección. Este panel estará compuesto por, como mínimo, tres personas, asegurando una representación de mujeres de 1/3, o de al menos el 25% de las personas del panel.
De acuerdo con los principios de OTM-R, se forma un panel de contratación con equilibrio de género para cada vacante al inicio del proceso. Después de revisar el contenido de las solicitudes, el panel comenzará las entrevistas, con al menos una entrevista técnica y una de competencias. Como mínimo, se realizará un cuestionario de personalidad, así como un ejercicio técnico durante el proceso.
El panel tomará una decisión final y todas las personas que hayan participado en la fase de entrevistas recibirán feedback con detalles sobre la aceptación o desestimación de su perfil.