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Postdoc Researcher in The Area of Machine Learning
vor 1 Woche
Job Information:
Organisation/Company
- Scuola Universitaria Professionale della Svizzera Italiana (SUPSI)
Research Field - Computer science » Programming
- Mathematics » Mathematical analysis
- Chemistry
Researcher Profile - First Stage Researcher (R1)
Country - Switzerland
Application Deadline - 02/04/ :58 (Africa/Cairo)
Type of Contract - Temporary
Job Status - Fulltime
Hours Per Week - 42
Offer Starting Date - 1/6/2023
Is the job funded through the EU Research Framework Programme? - Not funded by an EU programme
Is the Job related to staff position within a Research Infrastructure? - No
Offer Description:
The University of Applied Sciences and Arts of Southern Switzerland (SUPSI) has opened a full-time position for a
PostDoc Researcher in the area of machine learning,at the Department of Innovative Technologies (DTI) based at the USI-SUPSI university campus in Lugano-Viganello (East Campus), within the
Dalle Molle Institute for Artificial Intelligence (IDSIA).
You will carry out research within the EU-funded project PRAESIIDIUM, in collaboration with an outstanding team of academic, medical and industrial partners from all over Europe.
We will develop a prototype tool for real-time prediction of the pre-diabetic risk based on the integration of patient-specific mathematical models and a rich dataset of real-life data.
The approach will rely on novel
physics-informed machine learning (ML) techniques in order to overcome the limits of standard "black-box" ML practice, while reducing the computational time for simulating heavy numerical models and improving their prediction performances.
Requirements:
Research Field
- Physics
Education Level
Skills/Qualifications
- Perform innovative fundamental research on physicsinformed machine learning, probabilistic modelling and deep learning.
- Contribute to the acquisition of grants for both applied and basic research projects.
- Possibility to teach.
Specific Requirements
- Proven research experience on mathematical modelling, ordinary and partial differential equations, dynamical systems, machine learning and/or related fields.
- Ph.
- Excellent programming skills with data science languages (R, Python) and libraries.
- Excellent mathematical skills.
- Good publication record.
Languages
- ENGLISH
Level
Additional Information:
Work Location(s):
Number of offers available
- 1
Company/Institute
Country
Switzerland
State/Province
Ticino
City
lugano - viganello
Postal Code
6962 Viganello
Street
Via la Santa 1
Geofield
Where to apply:
WebsiteContact**:
City
- Manno
Street - Stabile Le Gerre
Postal Code - 6928
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