PhD Position Rheumatic Digital Twin | Integrating Clinical and Omics Data – Delft University of Technology (TU Delft) – Delft

  • Delft

Delft University of Technology (TU Delft)

We are looking for a highly motivated candidate for a PhD project that focusses on the development of novel computational methods for the stratification of patients with inflammatory rheumatic disease by integrating patient data from the clinic and various types of omics resources.

In short

  • You will develop and apply integrative computational methods to propose novel phenotypic subtypes of inflammatory rheumatic disease and analyse various types of omics data to identify biomarkers that would guide the development of future diagnostic assays.
  • You will work in a highly multi-disciplinary environment ranging from data scientists to treating rheumatologists with the focus to develop and translate novel algorithms for patient stratification to a clinical setting.
  • You will actively disseminate your work by writing scientific manuscripts and presenting your research at international conferences.
  • The research

    Clinical need: Rheumatic diseases are chronic inflammatory conditions affecting joints and cartilage and are characterized by their progressive and disabling nature. Rheumatic diseases display a wide heterogeneity stemming from complex interactions between genetics and environmental factors, and frequently lead to chronic autoimmune responses causing severe joint and cartilage damage. A timely recognition of rheumatic diseases in all its subtypes is therefore essential.

    Ongoing work: In close collaboration with the dept. of Rheumatology of the Leiden University Medical Centre, we work on the development of algorithms to stratify incoming patients with suspect rheumatic disease using large resources of observational and routine diagnostic data. We are proud to do this as a partner in a European Union-funded SPIDeRR consortium () using data from general practitioners and hospitals throughout Europe.

    Your project: Within our consortium, we set out to evaluate various omics data types such as auto-antibody panels, NMR metabolomics, and RNA sequencing for their potential to enhance the speed and accuracy of IRD diagnoses. For this purpose, you will complement routine diagnostic data with omics data and compute patient-patient similarities to comprehensively map the entire spectrum of IRDs into a landscape of IRD patients, referred to as the ‘inflammatory Rheumatic Digital Twin (iRDT)’, which can be used to guide the diagnosis and treatment of future patients. Next to the developing the methods to integrate the data, you will investigate: 1) to what extent do omics resources underpin patient stratifications obtained using an iRDT based on routine diagnostic data only; 2) whether your patient groupings are more informative on treatment outcomes; and 3) what molecular mechanisms differ between the data-driven patient groupings.

    Specifications

  • 36—40 hours per week
  • €2770—€3539 per month
  • Delft
  • Delft University of Technology (TU Delft)

    Requirements

    You hold a MSc degree in bioinformatics, computer sciences, statistics, life sciences or a similar area. You possess a strong background in data analytics and machine learning methods. You enjoy gaining, combining, and translating knowledge from multiple fields and have an optimistic and kind nature.

    Doing a PhD at TU Delft requires English proficiency at a certain level to ensure that the candidate is able to communicate and interact well, participate in English-taught Doctoral Education courses, and write scientific articles and a final thesis. For more details please check the .

    Conditions of employment

    Fixed-term contract: 4 years.

    Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2,5 years assuming everything goes well and performance requirements are met.

    Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2770 per month in the first year to € 3539 in the fourth year. As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.

    The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.

    For international applicants, TU Delft has the . This service provides information for new international employees to help you prepare the relocation and to settle in the Netherlands. The Coming to Delft Service offers a for partners and they organise events to expand your (social) network.

    The project will be conducted at the Pattern Recognition & Bioinformatics group from the Delft University of Technology, led by Prof. Marcel Reinders, under daily supervision of Dr. Erik van den Akker. Both are also appointed at the Leiden Computational Biology Center (LCBC) of the Leiden University Medical Center, aimed at developing and applying state-of-the-art data science techniques in the biological and medical domain. The project is in close collaboration with the department of rheumatology led by prof Tom Huizinga and embedded within the rheumatology data science lab led by Dr. Rachel Knevel, who also recently joined the LCBC. We have weekly multi-disciplinary work discussions featuring data scientists, epidemiologists, statisticians, and medical doctors.

    Employer

    Delft University of Technology

    Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context.

    At TU Delft we embrace diversity as one of our core and we actively to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale. That is why we invite you to apply. Your application will receive fair consideration.

    Challenge. Change. Impact!

    Department

    Faculty Electrical Engineering, Mathematics and Computer Science

    The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) brings together three scientific disciplines. Combined, they reinforce each other and are the driving force behind the technology we all use in our daily lives. Technology such as the electricity grid, which our faculty is helping to make completely sustainable and future-proof. At the same time, we are developing the chips and sensors of the future, whilst also setting the foundations for the software technologies to run on this new generation of equipment – which of course includes AI. Meanwhile we are pushing the limits of applied mathematics, for example mapping out disease processes using single cell data, and using mathematics to simulate gigantic ash plumes after a volcanic eruption. In other words: there is plenty of room at the faculty for ground-breaking research. We educate innovative engineers and have excellent labs and facilities that underline our strong international position. In total, more than 1000 employees and 4,000 students work and study in this innovative environment.

    Click to go to the website of the Faculty of Electrical Engineering, Mathematics and Computer Science.

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