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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.
This position involves developing and applying LLM-based approaches to enhance the accessibility, accuracy, and impact of climate-related information, bridging the gap between scientific research and broader audiences.
The selected candidate will work on cutting-edge AI research in collaboration with leading experts in machine learning and climate science, contributing to European and applied research projects. They will have the opportunity to explore innovative AI-driven methods for processing and generating climate-related content, ensuring that complex scientific findings are effectively communicated to policymakers, researchers, and the public.
We seek highly motivated applicants with proven experience in machine learning and LLMs, a strong interest in applied research, and a passion for leveraging AI to address global challenges.
The position offers access to expert training, a multidisciplinary research environment, and BSC-CNS staff benefits, providing an excellent opportunity for career growth in AI for climate science.
- Develop and apply large language models for science communication, improving the accessibility and clarity of climate-related information.
- Design and implement machine learning models to process, summarize, and generate climate science content for diverse audiences, including researchers, policymakers, and the public.
- Conduct experiments and evaluations to assess the effectiveness of LLM-driven approaches in science communication and refine models based on feedback.
- Participate in the BSC contributions to several project deliverables
- Design and create a large-scale dataset of climate information to be used for training and finetuning machine-learning models
- Evaluate the performance of different machine learning models in the communication of climate information
- Contribute to scientific publications in high-impact journals and conferences to present the research findings
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Education
- Bachelor's or master's degree in Computer Science, Artificial Intelligence, Machine Learning, Computational Linguistics, or a related field.
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Essential Knowledge and Professional Experience
- Proven experience in developing and applying Large Language Models (LLMs), including fine-tuning and prompt engineering.
- Experience with data preprocessing, model evaluation, and optimization techniques for language models.
- Strong background in machine learning and deep learning frameworks such as PyTorch or TensorFlow.
- Proficiency in Python and experience with NLP libraries (e.g., Hugging Face Transformers, spaCy, NLTK).
- Familiarity with climate science concepts or a strong willingness to learn about climate-related challenges.
- Ability to work in an interdisciplinary team, collaborating with AI researchers, climate scientists, and science communicators.
- Excellent communication skills, with the ability to explain complex AI models and results to non-expert audiences.
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Additional Knowledge and Professional Experience
- Experience in scientific communication, knowledge distillation, or AI-driven text generation.
- Experience working on European or international research projects.
- Publications in peer-reviewed conferences or journals
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Competences
- Problem-solving, pro-active, result-oriented work attitude
- Capability to work in an international and fast-paced work
- Good written and verbal communication skills in English
- Ability to work in a professional environment within a multidisciplinary and international team
- The position will be located at BSC within the Earth 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, support to the relocation procedures
- Duration: Open-ended contract due to technical and scientific activities linked to the project and budget duration
- Holidays: 23 paid vacation days plus 24th and 31st of December per our collective agreement
- Salary: we offer a competitive salary commensurate with the qualifications and experience of the candidate and according to the cost of living in Barcelona
- Starting date: As soon as possible
- 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.
At BSC, we seek continuous improvement in our recruitment processes. For any suggestions or comments/complaints about our recruitment processes, please contact recruitment [at] bsc [dot] es.
For more information, please follow this link.
BSC-CNS is an equal opportunity employer committed to diversity and inclusion. We are pleased to consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or any other basis protected by applicable state or local law.
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