PhD Student

Last application date
Aug 31, 2024 00:00
TW05 - Department of Information Technology
Limited duration
Master's degree in computer science, Mathematics, Artificial Intelligence, or equivalent
Occupancy rate
Vacancy type
Research staff

Job description

PhD Researcher in Adaptive Deep Neural Networks for Robotic Sensing

The IDLab Ghent research group is seeking a highly motivated and talented PhD student to join the distributed machine learning team. Our team focuses on developing efficient machine learning algorithms for perception and control; with diverse applications in industry, robotics, remote sensing and agriculture. As part of our ongoing research, we identified a trend towards adaptive techniques for deep neural networks. These techniques dynamically adjust the computational cost of processing new input samples, based on factors such as input complexity, desired accuracy, or remaining battery capacity. This approach, compared to traditional architectures with fixed inference paths, proves to be more efficient in terms of latency and energy consumption, especially for resource-constrained devices like embedded compute platforms on drones and robots. As these devices operate in diverse or changing conditions, the models should support some sort of adaptive inference paths with early-exit mechanisms, or continuous learning mechanism to adapt to changing input data distributions and conditions.
In this PhD, you will be focusing on autonomous systems that use complex machine learning models to extract information from high-rate, high-dimensional sensors such as radar or hyperspectral cameras. You will design novel architectures with flexible inference paths and/or self-learning capabilities.

The PhD is part of the ambitious Flanders AI Research program ( Within this context, you will be able to interact with many fellow PhD students and industry stakeholders throughout Flanders.

Your main tasks include:

  • Reviewing literature on efficient deep neural network methods, adaptive inference and self-learning techniques.
  • Designing and implementing transformer-based models for real-time processing of high-dimensional sensor data (radar, hyperspectral).
  • Developing techniques for efficient inference and continuous learning of deep neural network architectures. These designs should be informed by the specific hardware configuration of embedded platforms.
  • Cooperating with domain experts in areas such as agriculture and remote sensing in order to build proof-of-concept demonstrations of novel sensing solutions on AI accelerators.
  • Writing high quality publications, targeting top journals and international conferences.

In addition to your primary research responsibilities, you will actively contribute to the educational mission of our institution by providing support for various courses in areas such as machine learning and algorithm design. In addition, you can take on a mentoring role by supervising master theses related to the subject of this PhD.

We offer the opportunity to do this research in an international and stimulating environment. Ghent University consistently ranks among the best 100 universities in the world. Located in the heart of Europe, Ghent is a beautiful and welcoming city ( with plenty of cultural and leisure activities.

The selected candidate will be offered a 4-year employment, with an intermediate evaluation after the first year (1+3 years). The salary is competitive and will be determined by the university salary scales. In addition, staff members can count on a number of benefits, such as a broad range of training and educational opportunities, 36 days of vacation leave, bicycle allowance, and more.

Job profile

We are looking for a highly creative and motivated PhD student with the following qualifications and skills:

  • You have (or will obtain in the next months) a (European) master's degree in computer science, Mathematics, Artificial Intelligence, or equivalent, with excellent ('honors'-level) grades. Your degree must be equivalent to 5 years of studies (bachelor + master) in the European Union.
  • You have a strong background in machine learning and are eager to advance the state-of-the-art in adaptive inference.
  • You have excellent computer science skills (python, git, linux, etc.)
  • You have hands-on experience with machine learning frameworks such as PyTorch or Tensorflow.
  • Experience with computer vision, remote sensing, drones, hyperspectral imaging or embedded compute platforms (e.g. NVIDIA Jetson, Edge TPU, …) is considered a strong plus.
  • You have strong analytical skills to interpret the obtained research results.
  • You are a team player and have strong communication skills.
  • Your English is fluent (C1 CEFR level) both speaking and writing.

How to apply

Send your application by email to Prof. Pieter Simoens ( and dr. Sam Leroux ( Applications should include

  • An academic/professional resume
  • Transcripts of study results
  • At least two reference contacts.
  • A short overview describing your earlier research or technical work (e.g., scientific papers, master thesis, report on project work, etc.). These documents need not be on the topic of the advertised position.

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