Vacancy: Researcher/PhD student - Machine Learning

(05-08-2019)

Last application date: September 30, 2019 12:00

Department: IDLab – Ghent University-imec

Contract: Limited duration, 4-5 years, i.e. to allow the candidate to obtain a PhD degree

Degree: Master’s degree, preferably in Computer Science, Electronics-ICT or Informatics

Occupancy rate: 100%

Vacancy Type: Junior research staff, PhD position

Job description

The IDLab research group of Ghent University - imec performs research in the area of preventive health and eHealth. This research focuses on the design of data analytics for clinical settings and home care. The research is typically performed in close collaboration between national and international partners from both academia (e.g. university hospital) and industry.

Preventive health: According to the WHO, modifiable lifestyle behaviours, e.g. tobacco use or physical inactivity, cause 80% of the non-communicable diseases (NCDs), e.g. cardiovascular disease or type 2 diabetes. Preventive healthcare, focussing on measures to modify a patient’s behavior in order to prevent diseases rather than treat them, can reduce premature deaths, improve quality of life, and reduce healthcare costs. Unfortunately, changing behavior is a difficult process requiring a combination of motivation, actions, capabilities and opportunities. Therefore, at IDLab, we perform research into Mobile health Behaviour Change Support Systems (hBCSS), e.g. fitness trackers, smart watches, wearable sensors and mobile applications, to monitor a person’s behavior and inform healthier lifestyle choices. More specifically, we perform research into how data analytics on the collected vast amounts of data can be used to accurately get a grasp on the behavior, profile, context and motivation of a person. We are particularly interested in how domain or expert knowledge (e.g. from a coach) can be used to enhance the performance of these data-driven data analytics algorithms. Moreover, these insights feed then the research into personalized and context-aware algorithm design, e.g., for stress or burn-out assessment, and triggering long-term engagement with the user.

eHealth: IDLab has an on-going (> 15 years) collaboration with Ghent University Hospital to perform research into decision support systems that enable more personalized healthcare. For this, research is performed into data analytics algorithms that predict or suggest possible diagnoses, patient progression and treatment plans. Particularly, the focus is on how the insights from the clinical parameters collected from the patient, can be optimally merged with other inputs, e.g., medical expert knowledge from the physicians, genome data, unstructured text, etc. The use cases we have worked on are optimizing antibiotic dosing, early birth risk prediction, early detection of sepsis, etc.

We are looking for a junior researcher to contribute to (inter-)national research projects on machine learning and data analytics within the above described healthcare domains.

You will cooperate with enthusiastic colleagues and diverse external partners to fulfill the project requirements while staying up to date with important changes in the related literature. Projects will allow you to collaborate with researchers and developers from Europe and beyond in the area of machine learning for preventive health and eHealth. You will be given the opportunity to work on new machine learning technologies that will facilitate predictive modeling, anomaly detection, and root cause analysis. You will work on both European and regional research projects on this topic. Experience with semantic reasoning is a plus.

Profile of the candidate

Requirements:

  • A master’s degree, preferably in Computer Science, Electronics-ICT or (Mathematical) Informatics;
  • Fluent in English, both speaking and writing;
  • You are a proficient programmer, especially in Python. You have proven experience in software or algorithm development (e.g. student projects or master thesis successfully completed);
  • You should have a strong interest in machine learning, signal processing, time series analysis, and/or semantic reasoning;
  • An open mind and a multi-disciplinary attitude is a must;
  • You have analytical skills;
  • You are able to organize your work independently. You respect the predetermined milestones in research projects;
  • You have the ability to communicate your work in a comprehensible manner to a computer science audience.

How to apply

Send your motivation, scientific resume, academic results, the electronic version of your master thesis, relevant publications if applicable, and two reference contacts to prof. dr. ir. Sofie Van Hoecke (Sofie.VanHoecke@UGent.be) and dr. Femke Ongenae (Femke.Ongenae@UGent.be). After the first screening, suitable candidates will be invited for an interview (also possible via Skype).

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