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Postdoc in Federated Learning
il y a 2 semaines
Postdoc in Federated Learning & Analysis for Health Research:
- Employer
- LCSB
- Luxembourg Centre for Systems Biomedicine
- Location
- Luxembourg, Esch-sur-Alzette
- Salary
- Negotiable
- Closing date
- 26 May 2024
- Discipline
Job Type
Postdoctoral
Employment - Hours
Full time
Duration
Fixed term
Qualification
PhD
Sector
Academia- You need to sign in or create an account to a job.
- Job Details
- Company
Job Details:
About us...
The
Luxembourg Centre for Systems Biomedicine (LCSB) is an interdisciplinary research centre of the University of Luxembourg.
We conduct fundamental and translational research in the field of Systems Biology and Biomedicine - in the lab, in the clinic and _in silico_.
We focus on neurodegeneration and are especially interested in Alzheimer's and Parkinson's disease and their contributing factors.The LCSB recruits talented scientists from various disciplines. Computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently work at the LCSB. We excel because we are truly interdisciplinary and together, we contribute to science and society.
Your Role...
- **Develop federated analytical workflows**: integrate and adapt federated learning workflows specifically designed for health research, emphasizing scalability, efficiency, and privacy
-
:
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Generate and use synthetic data: create synthetic data using methods like GANs for use in federated analysis, ensuring the data is both realistic and privacy compliant
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Support the development of federated data management and analysis platform: actively engage and support the platform development team in implementing federated analytical workflows into the CLINNOVA platform
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Take an active role on project activities: take charge of specific project activities, working in close harmony with a multidisciplinary team to meet project goals effectively
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Disseminate research findings: actively share the ongoing work and findings with the project members, the scientific community and other stakeholders through project meetings, conferences and publications
What we expect from you
Required qualifications:
- A PhD in computer science, information technology, computational biology, bioinformatics, or a related field, with keen interest in health research and related IT infrastructure
- Domain knowledge:
- Good understanding of statistical analysis principles and AI/ML techniques in both centralized and federated environments
- Handson experience in developing, deploying, and maintaining ML operations (MLOps) within IT infrastructure, including familiarity with virtualization and containerization technologies such as Docker and Kubernetes is considered advantageous
- Technical skills:
- Proficiency in Python programming language, including data manipulation libraries (e.g., Pandas), ML frameworks (e.g., scikitlearn), and visualization tools (e.g., Matplotlib, Seaborn)
- Familiarity with federated technologies, such as Flower, NVIDIA FLARE, is considered advantageous
- Additional skills:
- Good ability to manage tasks effectively to meet project deadlines and reporting
- Experience with authentication and authorization solutions (e.g., ELIXIR-AAI, OIDC, GA4GH), cloudbased AI/ML services, testing methodologies (unit, integration, e2e) is considered advantageous
Here's what awaits you at the LCSB...
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Excellent work environment with state-of-the-art infrastructure, laboratory and administrative support
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Truly connected. We work together with hospitals and research institutes on a national and international level as well as industrial partners. Connection between science and society is very important to us. From our school lab - the Scienteens Lab - to the different outreach activities and collaborative partnerships with patient associations, we love to listen to society's needs and share our passion for science
-
Be part of a multicultural team. At the LCSB we have more than 50 nationalities. Throughout the year, we organise team-building events, networking activities and more
Find out more about us
Applications (in English) should be submitted online and include:
- A detailed curriculum vitae (CV) including a list of publications and projects
- A cover letter describing experience and future interests
- Contact information and recommendation letters from at least three referees
We are fully committed to removing any discriminatory barrier related to gender, and not only, in recruitment and career progression of our staff.
General information:
- Contract type: Fixed Term Contract 36 Month (extension possible)
- Work hours: Full Time 40.0 Hours per Week
- Location
- Job reference: UOL06363
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