Postdoc Translational AI Laboratory: graph machine learning

12 Mar 2024
Job Information

Organisation/Company

Amsterdam UMC

Research Field

Physics

Researcher Profile

Recognised Researcher (R2)

Country

Netherlands

Application Deadline

26 Mar 2024 - 22:59 (UTC)

Type of Contract

Temporary

Job Status

Not Applicable

Hours Per Week

36.0

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

In recent years, many new directions in graph machine learning have been investigated. A major problem for all graph machine learning approaches, especially on rich datasets, is incompleteness. In large knowledge graphs, there is always missing information, and even some of the included information might be wrong. Complex query answering is an active area of research trying to deal with these problems by answering queries about the graph as if the graph were complete. To do so, the approaches must predict the set of correct answers. While several approaches have been investigated by now, they all deal with rather simple knowledge graphs. They do not deal with attributes of various modalities and these methods cannot take human input into account, nor can explanations be provided on how results came to be.

You will develop and analyze new graph machine learning methods in the context of neurological disorders, specifically leukodystrophies, which are about degeneration of white matter in the brain. This research aims to identify features (biomarkers) that predict the course of adrenoleukodystrophy (ALD). We do this as part of our overall pursuit to unravel the pathophysiology of ALD, which would elucidate pathways involved in its pathogenesis and could potentially guide therapy development. This research will benefit hugely if clinical knowledge graphs can be used by physicians to interactively query potential associations between biomarkers during the diagnosis, prognosis and treatment phases with a system that can also provide clear explanations.

The project is an industry-sponsored collaboration between the Translational AI Laboratory (TrAIL) at the Department of Laboratory Medicine of Amsterdam UMC and the Learning and Reasoning (L&R) group at the Department of Computer Science of the VU University Amsterdam. You will be working in both the TrAIL and L&R research groups, in close collaboration with other laboratory medicine researchers and clinicians in pediatric neurology.
Your challenges will be to (1) develop new graph machine learning methods based on complex query answering and by enabling these methods to incorporate human input, and (2) apply the newly developed methods for medical knowledge discovery in the understanding, diagnosis and treatment of adrenoleukodystrophy. You will actively contribute to the growing body of knowledge on advanced AI models and methods in healthcare; foster and enable the clinical implementation of impactful medical risk models; and deliver first steps towards deploying cutting-edge graph ML models in practice to improve future medical decision-making.

Requirements
Specific Requirements

• PhD in artificial intelligence, bioinformatics, computer science, or related fields;
• Affinity and experience with research in knowledge graphs;
• Affinity and experience with healthcare research, preferable in pediatrics and/or neurology;
• Organizational, communicative and cooperative skills, as you will collaborate with scientists from multiple scientific disciplines.

Additional Information
Benefits

• A contract for 18 months;
• Salary scale 10: € 3.359 - € 5.292 with a 36 hour week (depending on qualifications and experience).
• Besides a good basic salary, you will also receive an 8.3% year-end bonus and 8% holiday allowance.
• Free and unlimited access to our online learning environment GoodHabitz.
• Pension accrual with BeFrank, a modern, understandable, and well-priced pension.
• Excellent accessibility by public transport and reimbursement of a large part of your transport costs. We also have a good bicycle scheme if you cycle, and sufficient parking spaces in case you drive.
• An active personnel association and the Young Amsterdam UMC association, both of which organize fun (sports) activities and events.

Additional comments

The selection procedure will be performed in two rounds: the first being an interview, the second will be an assessment. We aim for this position to start on June 1, 2024.

If you have any questions about this position, please feel free to contact Prof. Martijn C. Schut via [email protected] or dr. Michael Cochez via [email protected] .

For more information about the application procedure, please contact Chey Edwards, Recruitment Advisor, via [email protected] or via +31 214 87 245.

A reference check, screening and hiring test may be part of the procedure. Read here whether that applies to you. If you join us, we ask you for a VOG (Certificate of Good Conduct).

Internal candidates will be given priority over external candidates in case of equal suitability.

Acquisition in response to this vacancy is not appreciated.

Website for additional job details

https://www.academictransfer.com/338886/

Work Location(s)

Number of offers available

1

Company/Institute

Amsterdam UMC

Country

Netherlands

City

Amsterdam

Postal Code

1105AZ

Street

Keizersgracht 555

Where to apply

Website

https://www.academictransfer.com/en/338886/postdoc-translational-ai-laboratory-…

Contact

City

Amsterdam Zuidoost

Website

https://www.amsterdamumc.org/

Street

Meibergdreef 9

Postal Code

1105 AZ

STATUS: EXPIRED