Postdoc positions in Machine Learning for biological data
Yourmission : We are looking for a highly motivated new team member to further develop data driven computational tools for biological data. Our group has several ongoing collaborations spanning the modelling of cellular processes, multi-omics data processing, graph-based machine learning for protein design, drug discovery …
Start date : The position is immediately available (winter/spring 2022) and start date is flexible. Term of employment : Fixed-term (CDD) Work rate : 100% Duration : Contract: 1 year, renewable, maximum 4 years.
Postdoc positions in Machine Learning for single molecule imaging and omics analysis of mRNA translation
This position is funded in the context of a collaborative SNSF Sinergia grant “Integrated multi-scale analysis of translation: single-molecules, omics and computation” with Jeff Chao (FMI Basel) and Felix Naef (EPFL).
Yourmission : We are looking for a highly motivated new team member to further develop data driven computational tools for biological data, in particular the analysis and modeling of single-molecule translation experiments, i.e. advancing our understanding of how ribosomes work using machine learning models. More info
Start date : The position is immediately available (winter/spring 2022) and start date is flexible. Term of employment : Fixed-term (CDD) Work rate : 100% Duration : Contract: 1 year, renewable, maximum 4 years.
Master Internship
Master Internship in “Ferroelectric junctionless FET for memory and neuromorphic application”
EPFL EPFL, the Swiss Federal Institute of Technology in Lausanne, is one of the most dynamicuniversity campuses in Europe and ranks among the top 20 universities worldwide. The EPFL employs more than 6,000 people supporting the three main missions of the institutions: education, research and innovation. The EPFL campus offers an exceptional working environment at the heart of a community of more than 16,000 people, including over 12,000 students and 4,000 researchers from more than 120 different countries.
NANOLAB The Nanoelectronic Devices Laboratory (NANOLAB) is working on research topics in advanced nanoelectronics, with special emphasis on the technology, design and modeling of nanoscale solid-state devices. The group is interested in exploring new materials, novel fabrication techniques, and novel device concepts for future applications in energy efficient Edge Artificial Intelligence, Internet-of-Things and Quantum Computing.
Your Mission NANOLAB Laboratory at the Ecole Polytechnique F d rale de Lausanne (EPFL) has an opening for a 6 months master student internship to investigate the Ferroelectric junctionless FET for memory and neuromorphic application. You will be involved in designing, fabricating, and electrically characterizing a junctionless FET with HfO2-based ferroelectric.
Your Profile The desired qualifications (not strictly required, but beneficial) are basic theoretical knowledge of cleanroom fabrication and electronic devices.
Contact If you are interested, please, send your CV to the following email addresses: carlotta.gastaldi [at] epfl.ch or nataliya.yakymets [at] epfl.ch
Research, PhD and Postdoc: ELISE Mobility Programs
1. Mobility program for experienced researchers The goal of the ELISE Mobility Program for Experienced Researchers is to bring ELISE/ELLIS Fellows, Scholars, and Members together by supporting their short and long-term scientific visits to initiate collaboration within the ELISE/ELLIS community. More information and application
2. Mobility program for phds and postdocs The PhD and Postdoc mobility program is aimed at existing PhD students and postdocs in the network who want to initiate a collaboration with a Fellow or Member at another site. Young researchers can give their careers a head start by gaining international experience and exchanging ideas with the best labs in Europe. The Mobility Award covers travel costs of up to 2,500 EUR per researcher over the duration of their PhD or postdoc.
A series of student projects associated to the CIS Collaboration Grant on Intelligent Assistive Robotics are now open! These projects aim to address additional research topics within the project or to implement related technological bricks. Several labs and research groups are typically involved in the supervision of these project, which allows students to gain multidisciplinary experience in research and development.
Interpretable Deep Learning towards cardiovascular disease prediction
Cardiovascular disease (CVD) is the leading cause of death in most European countries and is responsible for more than one in three of all potential years of life lost. Myocardial ischemia and infarction are most often the result of obstructive coronary artery disease (CAD), and their early detection is of prime importance. This could be developed based on data such as coronary angiography (CA), which is an X-ray based imaging technique used to assess the coronary arteries. However, such prediction is a non-trivial task, as i) data is typically noisy and of small volume, and ii) CVDs typically result from the complex interplay of local and systemic factors ranging from cellular signaling to vascular wall histology and fluid hemodynamics. The goal of this project is to apply advanced machine learning techniques, and in particular deep learning, in order to detect culprit lesions from CA images, and eventually predict myocardial infarction. Incorporating domain specific constraints to existing learning algorithms might be needed.
