Summary: We are inviting highly motivated candidates to apply for Postdoc Fellowships to join Professor Oliver Y. Chén's team. The team works on developing new machine-learning methods and statistical models to bridge the brain, behaviour, brain diseases, and brain-genome interface. We have open positions around: (a) building new machine-learning and statistical models, (b) brain-genome-brain diseases interface, and (c) digital health (see details below). Additionally, the Fellows have the freedom to develop independent studies within the broader aims of the Team and, if interested, can collaborate on other exciting internal and external projects. The Fellows will have joint affiliation with both the Lausanne University Hospital (CHUV) and the University of Lausanne.
Funding: The candidates are encouraged to first apply for competitive funding from national and international foundations. Securing one of these grants will help your career a great deal. Examples are the SNSF Swiss Postdoctoral Fellowships (SPF) 2023 (link for 2022; link 2; date for 2023 will be announced soon - please check regularly), and the Marie Skłodowska-Curie Actions (MSCA) Postdoctoral Fellowships (link 1; link 2; launch on 12 April 2023; deadline on 13 Sep 2023). We will provide you with support in your application and, subsequently, help with your transitioning and joining our team. If your applications were rejected and your case is outstanding and meets our team's goals, we will consider internal funding.
I. Contexte: What does our group do?
We work on developing new machine-learning and statistical methods and analyse data related to the brain, genes, and behaviour, in health and disease. Our data are recorded from diverse sources, from MRI machines to digital devices such as smartphones.
Our focus is threefold. (a) Building new, methodologically exciting models to address real-world problems. (b) Using these methods to investigate the interplays between the brain, genes, and behaviour, and when/how they cause diseases; to identify markers to diagnose and prognose patients; to predict disease severity cross-sectionally and longitudinally. (c) Translating our algorithms into affordable medical devices and free health apps.
The Fellows will work on several projects related to the following directions.
Building new machine learning methods and statistical models to, for example, link large-scale brain data with multivariate disease/behaviour outcomes, and predict brain diseases and behaviour outcomes.
Brain - genome - brain diseases interface. Identify potential genetic features associated with disrupted brain functions and/or irregular structure. Use these genetic and neural markers to assess disease and behaviour outcomes.
Digital health. Design methods to empower digital devices, such as smartphones, to monitor or predict illnesses remotely and longitudinally.
The Fellows will, if interested, collaborate with colleagues in other projects within and across teams.
The Fellows have the freedom to develop independent studies within the broader aims of the Team and collaborate with or visit other teams in Asia, the EU, Switzerland, the UK, and the USA.
The Fellows will work in an interdisciplinary, multicultural environment with machine learning scientists, neuroscientists, geneticists, and clinicians.
The positions, once filled, may start immediately.
III. Profil: What are we looking for?
PhD or MD/PhD in a discipline relevant to machine learning, statistics, applied mathematics, biostatistics, engineering, or computer science.
A strong publication track record.
An interest in developing new methods and applications and employing them to address real-world problems.
An interest in data visualization.
A team player.
The working language of the group is English.
Strong programming skills in MATLAB, R, and/or Python.
Experience in machine learning algorithms, statistical modelling, and version control.
IV. Nous offrons: What do we offer?
Full support for your funding application. For strong but unlucky cases, potential internal funding.
A joint affiliation with the Lausanne University Hospital (CHUV) and the University of Lausanne.
An interdisciplinary environment, and a supportive team. We strive for equality, diversity, and inclusion. Our team is interdisciplinary and multicultural, and we encourage underrepresented students to apply.
Possibility to collaborate with and visit external colleagues at Johns Hopkins University, KU Leuven, University of Bristol, University of Oxford, University of Pennsylvania, Vrije Universiteit Brussel, and Yale University.
V. Contact et envoi de candidature: How to apply?
Please send Professor Oliver Y. Chén (email@example.com) the following.
A motivation letter (no more than one page).
Copies of your undergraduate and master’s theses.
Contact information for three references.