Postdoc in machine learning and reinforcement learning

Updated: 2 months ago
Deadline: 15 Apr 2024

13 Mar 2024
Job Information
Organisation/Company

Vrije Universiteit Amsterdam (VU)
Research Field

Technology
Researcher Profile

Recognised Researcher (R2)
Country

Netherlands
Application Deadline

15 Apr 2024 - 21:59 (UTC)
Type of Contract

Temporary
Job Status

Not Applicable
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 project aims at pushing the boundaries of machine learning and reinforcement learning with applications to healthcare data. This project will develop state-of-the-art machine learning architectures tailored for temporal data. The goal will be to improve existing techniques such as off-policy evaluations in the context of reinforcement learning with both fundamental and applied contributions.

The application on epidemiological data will apply these innovative methodologies to refine our understanding of how environmental factors interact with intrinsic capacity, ultimately shaping functional outcomes in older adults.

  • you’ll develop new algorithms and characterize their properties with theoretical and experimental techniques.
  • you’ll apply these algorithms on real-world data with applications to healthcare.
  • you'll be at the forefront of an interdisciplinary research, driving innovation through your expertise in machine learning and reinforcement learning.

Requirements
Specific Requirements
  • a PhD in a relevant area of machine learning with either a focus on the fundamental aspects of machine learning or experience with healthcare data
  • able to function well both in a multidisciplinary team as well as independently and possess good communication skills
  • knowledge of python and relevant machine learning packages including deep learning
  • willingness to develop new machine learning algorithms and apply them in the context of healthcare data

As a university, we strive for equal opportunities for all, recognising that diversity takes many forms. We believe that diversity in all its complexity is invaluable for the quality of our teaching, research and service. We are always looking for talent with diverse backgrounds and experiences. This also means that we are committed to creating an inclusive community so that we can use diversity as an asset.

We realise that each individual brings a unique set of skills, expertise and mindset. Therefore we are happy to invite anyone who recognises themselves in the profile to apply, even if you do not meet all the requirements.


Additional Information
Benefits

This position is for a 12 month period starting at June 1st, 2024.

  • a salary of minimum € 3.226,00 (Scale 10) and maximum € 5.090,00 (Scale 10) gross per month, on a full-time basis. This is based on UFO profile Researcher 4. The exact salary depends on your education and experience.
  • a position for at least 1 FTE. Your employment contract will initially last 1 year.

We also offer you attractive fringe benefits and regulations. Some examples:

  • A full-time 38-hour working week comes with a holiday leave entitlement of 232 hours per year. If you choose to work 40 hours, you have 96 extra holiday leave hours on an annual basis. For part-timers, this is calculated pro rata.
  • 8% holiday allowance and 8.3% end-of-year bonus
  • solid pension scheme (ABP)
  • contribution to commuting expenses
  • optional model for designing a personalized benefits package

Additional comments

Are you interested in this position and do you believe that your experience will contribute to the further development of our university? In that case, we encourage you to submit your application.

Submitting a diploma is part of the application process.

Applications received by e-mail will not be considered.

Acquisition in response to this advertisement is not appreciated.


Website for additional job details

https://www.academictransfer.com/338925/

Work Location(s)
Number of offers available
1
Company/Institute
Vrije Universiteit Amsterdam
Country
Netherlands
City
Amsterdam
Postal Code
1081HV
Street
De Boelelaan 1111
Geofield


Where to apply
Website

https://www.academictransfer.com/en/338925/postdoc-in-machine-learning-and-rein…

Contact
City

Amsterdam
Website

http://www.vu.nl/
Street

De Boelelaan 1105
Postal Code

1081 HV

STATUS: EXPIRED

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