Job Reference
546_24_LS_MLBR_R2
Position
Large Language Models for Multimodal Synthetic Data Generation and Evaluation in Biomedicine (R2) - AI4S
Closing Date
Monday, 30 September, 2024
Reference: 546_24_LS_MLBR_R2
Job title: Large Language Models for Multimodal Synthetic Data Generation and Evaluation in Biomedicine (R2) - AI4S
About BSC
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, 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 under one roof, and currently has over 1000 staff from 60 countries.
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 Machine Learning for Biomedical Research unit at the BSC, led by Dr. Davide Cirillo, is currently offering a postdoctoral researcher position. This role focuses on exploring the potential of Large Language Models (LLMs) in generating multimodal synthetic data and evaluating their quality, with an emphasis on their application in clinical settings. It involves implementing models ensuring explainability and bias mitigation strategies. Additionally, the role includes the development of user-centric evaluation approaches to ensure that the models meet the highest standard for healthcare applications.
The researcher will operate within a sophisticated HPC environment, with access to cutting-edge systems and computational infrastructures. The role involves extensive collaboration with both international and local experts across public and private sectors. The researcher will develop and implement systems for creating synthetic datasets, which will be pivotal for training and evaluation processes.
Applicants should possess a robust understanding of a broad spectrum of biomedical data and be proficient in deep learning techniques. Familiarity with privacy-preserving AI and explainable AI (XAI) is preferred, enabling the development of innovative and ethically sound AI solutions.
This position offers an exceptional opportunity to contribute to significant advancements in AI-driven biomedical research, working in a dynamic and collaborative international research environment.
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
Key Duties Develop computational solutions, with special emphasis on AI methods, specifically LLMs, for the generation of synthetic instances of biomedical data of different types and modalities. Implement robust and reliable state-of-the-art generative models, such as Transformers, Diffusion models, Variational Autoencoders (VAE), Generative Adversarial Networks (GAN). Interact efficiently with the HPC environment of the Barcelona Supercomputing Center. Explore the application of explainability to the required tasks. Establish and maintain collaborations with national and international researchers in both the public and private sector in the area of healthcare and biomedical research. Requirements Education
PhD in computer science or bioinformatics with a very strong AI component. Essential Knowledge and Professional Experience
Experience in AI methodologies, specifically biomedical data analysis. Deep learning frameworks (PyTorch, TensorFlow) Interest in the life sciences area Capacity to explore new research lines Additional Knowledge and Professional Experience
Experience in synthetic data generation Knowledge and experience in life sciences research Knowledge and experience in machine learning and data science:
Data pre/post-processing (feature selection, feature reduction, plotting and visualization) Supervised and unsupervised learning (classification, regression, clustering) Model deployment and scaling strategies (Docker, Kubernetes) Programming: Python (scikit-learn, numpy, matplotlib), R, Java, C, C++, Git. Fluency in English is essential. Proficiency in Spanish and other European languages would be advantageous. Competences
Good communication and presentation skills Ability to work both independently, within a team and in a multi-cultural environment. 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: 45.000,00€ 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. 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.
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.
Deadline The vacancy will remain open until a suitable candidate has been hired. Applications will be regularly reviewed and potential candidates will be contacted.
OTM-R principles for selection processes BSC-CNS is committed to the principles of the Code of Conduct for the Recruitment of Researchers of the European Commission and the Open, Transparent and Merit-based Recruitment principles (OTM-R). This is applied for any potential candidate in all our processes, for example by creating gender-balanced recruitment panels and recognizing career breaks etc.
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