All employment opportunities (vacancies, new positions) are advertised by broad categories: Academic, Research, Administrative and Technical staff.
Università della Svizzera italiana
Call for candidates to apply to the SNSF Eccellenza and Ambizione Programs
The Università della Svizzera italiana (USI) welcomes excellent candidates to the two programs of the Swiss National Science Foundation (SNSF): Ambizione and Eccellenza.
Call (pdf, 348 Kb)
Deadline for submitting applications:
- Ambizione: 1st of September (SNSF deadline 1st November).
- Eccellenza: 15th of October (SNSF deadline 1st February).
Università della Svizzera italiana
Faculty of Communication Sciences
Institute of Media and Journalism (IMeG)
Call for an Assistant Professor in Digital Journalism
Call (pdf, 36 Kb)
Deadline: Applications received by 15th September 2019 will be given priority.
Università della Svizzera italiana
Faculty of Economics
Call for an Assistant Professor in Organization Theory
Call (pdf, 32 Kb)
Deadline: Applications received by October 1st, 2019 will be given priority.
Università della Svizzera italiana
Faculty of Economics
Institute of Economics (IdEP)
Call for Post-Doctoral Position in Applied Microeconomics
Call (pdf, 68 Kb)
Università della Svizzera italiana
Institute of Oncology Research
A Four-year Postdoctoral fellowship
Call (pdf, 172 Kb)
Università della Svizzera italiana
Istituto Ricerche Solari Locarno (IRSOL)
PhD and Postdoctoral Position in Solar and Computational Physics
Call (pdf, 120 Kb)
Università della Svizzera italiana
Faculty of Informatics
Postdoc positions within ERC project: “Perceptually-Driven Optimizations of Graphics Content for Novel Displays”
Call (pdf, 80 Kb)
Università della Svizzera italiana
Faculty of Informatics
Ph.D. positions within ERC project: “Perceptually-Driven Optimizations of Graphics Content for Novel Displays”
Call (pdf, 80 Kb)
Università della Svizzera italiana
Faculty of Informatics
PhD position within SNSF project BEST "Beyond Screen readers and Alt Text - Designing Multisensory Alternative to Text for Different Reading Abilities”
Call (pdf, 84 Kb)
Università della Svizzera italiana
Faculty of Economics
Institute of Management and Organization (IMO)
PhD student position in Management stream of the PhD program in Economics
Call (pdf, 26 Kb)
Università della Svizzera italiana
Faculty of Informatics
Learning Faces from DNA – PhD in novel deep learning methods for facial genetics applications
Within the context of an interdisciplinary project we plan to develop and investigate a novel methodology for reconstructing faces from DNA based on geometric deep learning. The research is supported by a 4-year co-funded FWO/SNF Belgian-Swiss research grant, as well as additional funding from ERC and Google. We are looking for a bright and motivated scientist with background in computer vision/geometry processing/computer graphics/machine learning and interest in statistical and imaging genetics who is willing to start a PhD at the University of Lugano, Switzerland and KU Leuven, Belgium under the joint supervision of Prof. Dr. Michael Bronstein, Dr. Peter Claes, and Prof. Dr. Dirk Vandermeulen.
Project
The problem of recovering the geometric structure of the human face from DNA is an important instance of genotype-to-phenotype mapping, one of the Holy Grails of modern genetics. Successfully solving it leads to a breakthrough in many applications, ranging from personalized medicine to biometrics and forensics. For example, a better understanding of facial genetics will help in the delineation and diagnosis of clinical syndromes. Furthermore, in archaeology, ancient remains containing genetic material would allow us to reconstruct the faces of people who lived ages ago. Last but not least, the reconstruction of the face from DNA found at a crime scene could become a ground-breaking instrument that would allow to solve thousands of criminal investigations and cold cases.
However, the problem is complex involving the joint modeling of known and unknown associated genetic interactions with related facial features. To address this challenge, we are developing novel geometric deep learning methods (www.geometricdeeplearning.com) that deal with geometric data and integrate prior biological knowledge. Therefore, in this project we aim to merge image and geometry processing with imaging genetics and computational biology.
Environment
Successful candidates will be enrolled in a co-supervised PhD between the University of Lugano and KU Leuven. The candidate will be primarily stationed in Switzerland and will have mid- and long-term visits at the KU Leuven, Faculty of Engineering, division ESAT-PSI (https://www.esat.kuleuven.be/psi) and the Medical Image Research Center (MIRC) (https://mirc.uzleuven.be/MedicalImagingCenter/about.php) hosting one of the world’s leading labs in facial genetics. The research will be embedded in a very stimulating environment with state-of-the-art technical facilities and ample opportunities for interaction with various engineers, clinicians and experts on craniofacial genetics and geometric deep learning.
Profile
Ideal candidates should satisfy the following requirements:
- Have or should soon obtain a Master's degree in engineering, computer science, artificial intelligence, or equivalent.
- Strong mathematical background
- Strong background in computer vision/graphics and machine learning with a publication record in top conferences (CVPR, ICCV, NIPS, ICML, ICLR, SIGGRAPH, SGP)
- Preferably, background or interest in bioinformatics, computational biology, or statistical genetics.
- Excellent programming skills, especially in python
- Experience with programming in deep learning frameworks (TensorFlow, PyTorch, etc.)
- Good skills in oral and written English.
Interested?
For further information contact Michael.bronstein@usi.ch
Applications should include a short motivation letter, full CV (including a detailed transcript of university study results), and the names and contact information of at least two references.
Università della Svizzera italiana
Faculty of Informatics
The Faculty of Informatics provides an exciting environment in which to develop a research career. The successful student will gain a broad knowledge and understanding of the general field of informatics, as well as an in-depth specialization in an area of interest. Working with one or more members of the Faculty, the student will contribute original, useful, and scientifically valid ideas in their chosen area of research. In addition, the student will have an opportunity to participate in the educational mission of the Faculty. Current research interests of the Faculty include all aspects of software engineering, computer systems, information systems, algorithm design and verification.
Admission to the Ph.D. program is highly competitive. Applicants are admitted based on their research interests and experience, potential for success in the program, and compatibility with current needs of the Faculty. The official language of the Ph.D. program is English. In order to be admitted, the applicant must have completed a Masters degree in computer science, informatics, or a closely related field prior to joining the program.
Further information, including detailed application instructions, are available at https://www.inf.usi.ch/en/study-informatics/phd-doctoral-studies.
