PhD Student – Department of Data Analysis and Mathematical Modelling

Organisation/Company

Ghent University

Research Field

Computer science » Other
Engineering » Other
Mathematics » Probability theory
Computer science » Programming
Mathematics » Statistics

Researcher Profile

First Stage Researcher (R1)

Country

Belgium

Application Deadline

20 Feb 2024 – 22:59 (UTC)

Type of Contract

Temporary

Job Status

Full-time

Hours Per Week

38

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

Last application date Feb 20, 2024 00:00

Department LA26 – Department of Data Analysis and Mathematical Modelling

Contract Limited duration

Degree Master’s degree in (bio-)Engineering, Computer Science, Mathematics, Physics or equivalent

Occupancy rate 100%

Vacancy type Research staff

Job description

PhD position: Spatio-temporal machine learning

– About the research unit
The research unit KERMIT (Knowledge-based Systems, https://kermit.ugent.be/ ) adopts a holistic view on mathematical and computational modelling, acknowledging the needs of our modern information society with a particular focus on the applied biological sciences. It strives to keep a unique balance between theoretical developments and practical applications, a strategy that has proven particularly successful, regarding the output, visibility and recognition of the team. It plays a pioneering role by promoting existing as well as developing new methods in a broad range of disciplines.

– Job description
The activities of the Ph.D. position are embedded in this research unit with a focus on the development of spatio-temporal machine learning methods. The proposed Ph.D. research is defined within the context of the Flanders AI Project (FAIR2).

Our natural environment evolves both in space and time. Modeling these spatio-temporal dependencies accurately is key to the development of trustworthy (data-driven) forecasting methods. This PhD topic focuses on the development of machine learning (ML) techniques for spatio-temporal modeling tailored to the needs of typical environmental modeling challenges. In contrast with big-data applications of ML, we consider settings in which datasets are typically small and sparse (in space and/or time). To compensate for the lack of data, this PhD topic will focus on knowledge integration spatio-temporal ML (known as knowledge guided ML). Moreover, we will study how these models can be optimized for their intended use in down-stream decision-making tasks (decision-focused learning).

As a Ph.D. candidate, you will be involved in the development of these methods, and their application for environmental modeling. Furthermore, you will publish your research results at major international conferences and in journal papers, as part of meeting the requirements for your Ph.D.

For more detailed information on this vacancy, contact Prof. Bernard De Baets ([email protected] ) or Prof. Jan Verwaeren ([email protected] ). Please add “STML vacancy” in the subject of your email.

Job profile

• We are looking for highly creative and motivated Ph.D. students with the following qualifications and skills.
• You have (or will obtain in the next months) a (European) master’s degree in (bio) Engineering, Computer Science, Mathematics, Physics or equivalent, with excellent (‘honors’-level) grades.
• You have a strong background at least one of the following: probabilistic modelling, mathematical statistics or machine learning and are eager to advance the state-of-the-art.
• You have excellent computer science skills (python, git, etc.)
• Experience with machine learning frameworks such as PyTorch or Tensorflow is considered a plus.
• You have analytical skills to interpret the obtained research results.
• You are a team player and have strong communication skills.
• Your English is fluent, both speaking and writing.

WHAT WE CAN OFFER YOU

• We offer a full-time position as a doctoral fellow, consisting of an initial period of 12 months, which – after a positive evaluation, will be extended to a total maximum of 48 months.
• Your contract will start on March 1, 2024 at the earliest.
• The fellowship amount is 100% of the net salary of an AAP member in equal family circumstances. The individual fellowship amount is determined by the Department of Personnel and Organization based on family status and seniority. A grant that meets the conditions and criteria of the regulations for doctoral fellowships is considered free of personal income tax. Click here for more information about our salary scales
• All Ghent University staff members enjoy a number of benefits, such as a wide range of training and education opportunities, 36 days of holiday leave (on an annual basis for a full-time job) supplemented by annual fixed bridge days, bicycle allowance and eco vouchers. Click here for a complete overview of all the staff benefits  (in Dutch).

How to apply

Send your application by email to Ms. Ruth Van den Driessche and Prof. Jan Verwaeren ([email protected] and [email protected] ), indicating “Job Application: STML” in the subject. Applications should include (1) an academic/professional resume, (2) transcripts of study results, and (3) at least two reference contacts. After a first screening, selected candidates will be invited for an interview (also possible via Teams).
Application deadline: continuous evaluation until the vacancy is filled

Requirements

Research Field

Computer science

Years of Research Experience

1 – 4

Research Field

Engineering

Years of Research Experience

1 – 4

Research Field

Mathematics

Years of Research Experience

1 – 4

Research Field

Computer science

Years of Research Experience

1 – 4

Research Field

Mathematics

Years of Research Experience

1 – 4

Additional Information

Website for additional job details

https://academicpositions.com

Work Location(s)

Number of offers available

1

Company/Institute

Ghent University

Country

Belgium

City

Ghent

Postal Code

9000

Street

Sint-Pietersnieuwstraat 33

Where to apply

Website

https://academicpositions.com/ad/ghent-university/2024/phd-student-department-o…

Contact

City

Ghent

Website

http://www.ugent.be/en

Postal Code

9000

STATUS: EXPIRED