Research Manager on Privacy-Preserving Machine Learning for Drug Design and Personalized Medicine
STADIUS is an internationally leading research group in information processing through mathematical engineering in data-driven modeling and analytics, systems and control, signals, optimization, and applied fields. It is part of the Department of Electrical Engineering (ESAT), within the Group Science, Technology and Engineering of KU Leuven. STADIUS has built significant expertise over the years in machine learning for early drug discovery and personalized medicine, as well as privacy-preserving learning methods for these applications. It is precisely in this domain that the research manager will contribute to the research and valorization strategies of STADIUS.
You will ensure the daily scientific supervision of collaborative industrial projects with pharmaceutical and clinical partners.
You will design innovative algorithmic and IT solutions for novel machine learning challenges in drug design, drug discovery,and personalized medicine.
You will supervise the implementation of those solutions by PhD students and/or software engineers.
You will assist professors in technology transfer activities, including the preparation of spin-off projects.
You will actively respond to the calls for proposals made by the different funding organizations.
You will discuss with funding organizations and project partners the management, administrative, technical and financial aspects of ongoing and future projects.
You will be responsible for the follow-up of projects in close concertation with KU Leuven research and development.
You will build a multi-disciplinary network comprising both national and international academic research groups and industrial partners.
You will contribute to the recruitment of Master and PhD students by supervising the generation of new Master and PhD thesis proposals in the framework of the different academic programs, and by participating in recruitment activities.
You will assist professors in the guidance of both Master and PhD students.
You have a PhD in Mathematical or Electrical Engineering, or Computer science, with a proven record in machine learning andprivacy-preserving methods in drug design, drug discovery, and personalized medicine.
You have minimal5 years of experience after your PhD, including a strong track record of collaboration with the industry and of writing research proposals.
You have established a solid publication track record for your career stage.
Your expertise includes the development of novel Bayesian models and deep learning models.
This also includes GPU implementation of those methods (in PyTorch and/or TensorFlow) and the implementation privacy-preserving methods (such as Multi-Party Computation).
You have core application area expertise in chemoinformatics, chemogenomics, and high-throughput/high-content screening.
You have experience in the generation of intellectual property, such as preparing patent application or preparing information for a technology transfer office.
You have knowledge of national and international funding schemes in the domain of artificial intelligence for drug discovery and personalized medicine.
You have experience with project management and coaching of a research team.
You are creative, enthusiastic and have a strong commitment to research and technology transfer.
You can work both independently and as part of a multidisciplinary research team.
You have excellent knowledge of English, both in speaking and writing.
We offer a contract of indefinite duration in the research framework of KU Leuven.
KU Leuven - Universiteit