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PhD Position Improving Treatment of Metastatic Cancers

PhD position within the NWO project „Improving treatment of metastatic cancers through game theory and dynamical systems theory“

ongeveer 2 maanden geleden

Arbeidsvoorwaarden

Standplaats:
Mekelweg, Delft, Zuid-Holland
Dienstverband:
Tijdelijk contract / Tijdelijke opdracht
Uren per week:
38 - 38 uur
Salarisindicatie:
€ 2395 - € 3061 per maand
Opleidingsniveau:
WO

Functieomschrijving

Within a Dutch National Foundation (NWO) project „Improving treatment of metastatic cancers through game theory and dynamical systems theory“, carried out between the Department of Data Science and Knowledge Engineering (DKE) at Maastricht University and the Delft Institute of Applied Mathematics (DIAM) at the Delft University of Technology, we are looking for a suitable candidate for a fully funded 4-year PhD position. This PhD candidate, hosted at the Delft Institute of Applied Mathematics, will, in collaboration with other members of our team, apply Stackelberg Evolutionary Game (SEG) theory, to design the so-called evolutionary therapies for specific metastatic cancers. Such therapies should replace the current standard of care in metastatic cancers where the maximum tolerable dose of treatment or treatment combination is applied until cancer progression, which innevitably leads to the evolution of resistence in cancer cells. The research will be carried out under supervision of Dr. Johan Dubbeldam (DIAM) and Dr. Katerina Stankova (DKE), and in the collaboration with the „Center of excellence for evolutionary therapy“ within the Moffitt Cancer Center in Tampa, Florida, US, where new clinical trials on this type of therapy are being carried out. Therefore, visits to this center and workshops including researchers from there will be part of this project as well.

Tasks and responsibilities

The PhD candidate should:

  • Validate model parameters in game-theoretical models describing interaction of different types of cancer cells, with mice/patient data as an input
  • Analyze transient dynamics of the models and its stability properties
  • Find treatment protocols for these models using Stackelberg game theory and optimal control theory
  • Develop Model Predictive Control algorithms to be able to adjust the treatment protocols in real time, based on the difference between the model predictions and real measurements

This all will be done in collaboration with the supervisors and a postdoctoral candidate (at DKE), who will work on development of general SEG theory of cancer treatment.

Department
Research at Delft Institute of Applied Mathematics (DIAM) is conducted in six research groups: Analysis, Applied Probability, Mathematical Physics, Numerical Analysis, Optimisation, and Statistics. Our research on the construction and analysis of mathematical models related to science and engineering is both fundamental and applied in nature and is often inspired by technical and societal challenges. We have, for instance, tackled complex mathematical problems to develop a model for predicting the flow of ash pollution after a volcano eruption. To come up with innovative solutions we maintain intensive contact with other TU Delft departments, technological institutes and research departments.

Besides research, education is an important cornerstone of our department. We teach the Applied Mathematics BSc and MSc programmes, as well as mathematics courses within other programmes at TU Delft, and national programmes such as “MasterMath”. Together with KTH Royal Institute of Technology (Sweden) and the Technical University of Berlin (Germany) we have also initiated the international joint Master’s programme COSSE (Computer Simulations for Science and Engineering).

Functie-eisen

We value the great atmosphere at our institute and pride ourselves on our sense of community and the spirit of “getting things done together”, which we combine with mutual appreciation for individual success. To foster interaction and cooperation, we organize lunch seminars where colleagues from the various sections discuss their work, and we arrange an annual social activity where all staff members interact informally to get to know each other in a different setting. Our open and transparent way of communicating is reflected in the way we interact with one another and forms the basis for the way we work together to help each other achieve our goals as a team.

Requirements

We are looking for an enthusiastic ambitious candidate with an academic degree (MSc) in applied mathematics, operations research, or related field. Knowledge of game theory, dynamical systems theory, optimal control theory and/or data science is a plus.

We require:

  • Excellent analytical skills (demonstrated by the grades during study and quality of MSc thesis)
  • Proficiency in Python or Matlab
  • English proficiency (both oral and written)
  • Ability to work in a multidisciplinary and diverse team

Conditions

TU Delft offers PhD-candidates a 4-year contract, with an official go/no go progress assessment after one year. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2395 per month in the first year to € 3061 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 sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. For international applicants we offer the Coming to Delft Service and Partner Career Advice to assist you with your relocation.

Additional information

For information about the selection procedure, please contact Miriam Heemskerk MSc, HR-advisor, email: vacancies-eemcs@tudelft.nl.

All additional information about the vacancy can be obtained from Dr. Johan Dubbeldam (J.L.A.Dubbeldam@tudelft.nl) and Dr. Katerina Stankova (k.stankova@maastrichtuniversity.nl).