Postdoctoral Researcher – Synthetic data generation in digital pathology (R2)

Date limit
16-03-2022
Institution
Barcelona Supercomputing Center (BSC)

 

Job title: Postdoctoral Researcher – Synthetic data generation in digital pathology

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 a hosting member of the PRACE European distributed supercomputing infrastructure. 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 770 staff from 55 countries.
 
Context And Mission
 
The Computational Biology group, led by ICREA professor Alfonso Valencia, is looking for a postdoctoral researcher to work in the context of Artificial Intelligence (AI) approaches for the synthetic generation of biomedical data of different types and modalities (images, genomic, time series, texts).

The Life Sciences Department at the BSC integrates the independent research of senior scientists that work on various aspects of Computer Science applied to Life Sciences, ranging from healthcare applications of machine learning and AI to the use of High Performance Computing (HPC) for biomedical research. The Computational Biology group (http://life.bsc.es/compbio) is involved in multiple projects covering a wide range of topics, including computational systems biology, network science, digital medicine, structural biology.

The candidate will work in collaboration with senior researchers in the Computational Biology Group of the Life Sciences Department as well as other research groups at the BSC. The work is in the framework of the research lines of the group that are focused on applications of AI in Personalized Medicine, which include synthetic data generation, complex systems modelling, agent-based simulations, among others.

The Researcher will work in a highly sophisticated HPC environment, will have access to state-of-the-art systems and computational infrastructures, and will establish collaborations with experts in different areas both at international and local levels as well as from the public and private sector. The Researcher’s tasks will involve developing and deploying systems for the generation of synthetic datasets to be used for further tasks, such as training and evaluation. The Researcher is expected to be familiar with the analysis of a wide range of biomedical data and deep learning and, preferably, concepts of privacy-preserving AI (federated learning) and explainable AI (XAI).
 
Key Duties
  • Develop computational solutions, with special emphasis on AI methods, 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 Variational Autoencoders (VAE) and Generative Adversarial Networks (GAN).
  • Interact efficiently with the HPC environment of the Barcelona Supercomputing Center.
  • Explore the application of federated learning and explainability to the required tasks.
  • Demonstrate skills in scientific communication.
  • Establish and maintain collaborations with national and international researchers in both the public and private sectors in the area of healthcare and biomedical research.
Requirements
  • Education
    • PhD in computer science or bioinformatics with a very strong AI component.
    • Alternatively, an MSc on AI or Bioinformatics, with a strong computer science background, or background in applied mathematics/physics with demonstrated experience in AI methods.
  • Essential Knowledge and Professional Experience
    • Experience in AI methodologies, specifically biomedical data analysis and synthetic data generation.
    • Deep learning frameworks (PyTorch, TensorFlow).
    • Interest in the life sciences area.
  • Additional Knowledge and Professional Experience
    • 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 (Doker, Kubernetes)
    • Programming: Python (scikit-learn, numpy, matplotlib), R, Java, C, C++, Git.
    • Fluency in spoken and written English.
  • Competences
    • Capacity to use new software, understand new methods, or new follow new research lines.
    • Good communication and presentation skills.
    • Ability to work both independently and within a team.
Conditions
  • The position will be located at BSC within the Life Sciences Department
  • We offer a full-time contract, a good working environment, a highly stimulating environment with state-of-the-art infrastructure, flexible working hours, extensive training plan, tickets restaurant, private health insurance, fully support to the relocation procedures
  • Duration: Temporary - 1 year, renewable renewable
  • 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: asap
Applications procedure and process

All applications must be made through the form at the bottom of the BSC website and contain:

  • A full CV in English including contact details
  • A Cover Letter with a statement of interest in English, including two contacts for further references - Applications without this document will not be considered

    In accordance with the OTM-R principles, a gender-balanced recruitment panel is formed for every vacancy at the beginning of the process. After reviewing the content of the applications, the panel will start the interviews, with at least one technical and one administrative interview. A profile questionnaire as well as a technical exercise may be required during the process.

    The panel will make a final decision and all candidates who had contacts with them will receive a feedback with details on the acceptance or rejection of their profile.

    At BSC we are seeking continuous improvement in our recruitment processes, for any suggestions or feedback/complaints about our Recruitment Processes, please contact recruitment@bsc.es.

    For more information follow this link

 

Deadline
The vacancy will remain open until 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 planels and recognizing career breaks etc.
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.
For more information follow this link