فاند دکتری ریاضیات هلند
فاند دکتری ریاضیات هلند | این پوزیشن شامل دو دانشجوی دکترا است. این موقعیت بر جنبه های علوم محاسباتی و ریاضی تمرکز خواهد کرد. دومین موقعیت دکتری بیشتر بر تخصص و کاربرد تکنیک های سنتی اپیدمیولوژیک متمرکز است.
- سیستم های پیچیده
- ریاضیات کاربردی
- آمار کاربردی
- فیزیک آماری
- علوم محاسباتی
- رشته های مرتبط
امتیازت و مزایا:
ماهانه ۲۴۳۴ تا ۳۱۱۱ یورو
امتیازت و مزایا:
- کارشناسی ارشد در علوم سیستمهای پیچیده، علوم محاسباتی، ریاضیات کاربردی، آمار کاربردی، فیزیک آماری یا رشته های مرتبط؛
- تجربه در زبان های برنامهنویسی سطح بالا مانند پایتون؛
PhD Position Dynamic Symptoms Networks
We are seeking a PhD candidate to work on an exciting research project in an interdisciplinary team. You will focus on the use of computational and mathematical methods to address the increasing challenge posed by ‘multi-morbidity’, both computationally and theoretically, in collaboration with a more medicine-oriented PhD candidate.
In 2018, 5.4 million Dutchmen suffered from multi-morbidity, defined as the co-occurrence of two or more diseases. Treating the individual diseases in isolation leads potentially to high burden of treatment, overtreatment, and unforeseen interactions between symptoms, medicines, and/or therapies. For this reason, health care in the presence of multiple diseases demands a different approach than the traditional disease-centered focus. Clinical models for adequate diagnosis, prognosis, and treatment in the context of multi-morbidity are currently lacking. Common epidemiological methods to model multi-morbidity do not suffice because they do not take into account dynamic interactions between diseases.
There is a growing consensus that the complexities underlying the onset of disease states of an individual cannot be unraveled by traditional, reductionistic methods alone. A shift in research paradigm to computational science, complex systems, network thinking, and multivariate analysis is therefore imperative to move this field forward. Taking steps towards a new paradigm may, eventually, enable the design of more effective treatments for a large group of people.
The ultimate vision of the to-be-developed paradigm shift in this project is to take domain experts’ knowledge, patients’ experience, scientific literature, and data as an input; summarize the statistical/causal relations between various (bio-)medical variates and disease outcomes into what we call dynamic symptom networks; and finally assess to what extent diagnosis, prognosis, and treatment design based on such symptom networks would improve health care beyond the state-of-the-art disease-centered practice.
What are you going to do
This PhD position is part of a larger Dutch research grant under ZonMw, consisting of two closely collaborating PhD students. This position will focus on the computational science and mathematical aspects. The second PhD position will focus more on the domain expertise and application of traditional epidemiological techniques.
From a technical standpoint, you will focus specifically on identifying as well as modeling (mathematical/computational) the dynamics of multi-morbidities. This will be done through extending the concept of disease networks (see for instance https://www.nature.com/articles/s41540-020-00143-9 for an accessible introduction). The first manner in which we plan to extend it is to enrich the statistical associations, used as part of the method, with multivariate information-theoretic measures, specifically the relatively novel concept of synergistic information (see for instance https://www.mdpi.com/1099-4300/19/2/85). The second manner is to extend the network concept to a multiplex network, due to integrating different types of studies into a single analysis. Finally, we will attempt to identify causal links and causally important nodes in the networks by existing techniques (see https://www.nature.com/articles/s41467-019-10105-3 and http://rsif.royalsocietypublishing.org/content/10/88/20130568). All of this is to be integrated in a set of methods and tools, which the domain experts in our project can apply to (other) datasets. During the development of the theory, methods, and tools, you are expected to closely collaborate with domain experts in order to ensure relevance and validity of your approach.
Chronologically, your project will start with data analysis, think tank sessions, and group model building sessions. This will inform the computational and mathematical framework to generate plausible models and simulations of symptom-symptom networks, symptom-disease networks, and their combinations and projections. This is to be used to simulate hypothetical scenarios of increasing multi-morbidity and then assess to what extent the traditional disease-centered remains effective, and/or whether a new paradigm is needed to remain effective in the multi-morbid regime. Finally, since it is unlikely that the existing data sets are sufficiently rich to uniquely identify (causal) symptom models, this project will also involve uncertainty quantification and determining what properties of hypothetical new data sets will be decisive in increasing modeling accuracy.
What do we require of you
For this position you need:
- an MSc in Complex Systems Science, Computational Science, Applied Mathematics, Applied Statistics, Statistical Physics, or related disciplines;
- experience in high-level programming language(s) such as Python;
- affinity towards and good knowledge of network science (graph theory). Preferably with experience in computational modeling of networks, network processes, network flow dynamics, and/or calculating various network topological features;
- to enjoys interacting with domain experts from different disciplines and tackling an interdisciplinary problem by internalizing and subsequently integrating qualitative knowledge into novel theory, computational models, and/or quantitative analyses;
- to be trained in computational modeling techniques, such as (ordinary) differential equations, Markov dynamics, or cellular automata, and is trained in simulation techniques, such as Monte Carlo sampling;
- to be trained in basic (multivariate) statistical analysis and/or information theory;
- to be familiar with the concept of uncertainty quantification, forward propagation of uncertainty in models;
- affinity towards contributing to a more holistic, data-driven, and multi-scale approach to managing human disease.
CONDITIONS OF EMPLOYMENT
Fixed-term contract: 18 months.
A temporary contract for 38 hours per week for the duration of four years (the initial contract will be for a period of 18 months and after satisfactory evaluation it will be extended for a total duration of four years). This should lead to a dissertation (PhD thesis). We will draft an educational plan that includes attendance of courses and (international) meetings. We also expect you to assist in teaching undergraduates and master students.
The salary, depending on relevant experience before the beginning of the employment contract, will be €۲,۴۳۴ to €۳,۱۱۱ (scale P) gross per month, based on a fulltime contract (38 hours a week). This is exclusive 8% holiday allowance and 8.3% end-of-year bonus. A favourable tax agreement, the ‘۳۰% ruling’, may apply to non-Dutch applicants. The Collective Labour Agreement of Dutch Universities is applicable.
Are you curious about our extensive package of secondary employment benefits like our excellent opportunities for study and development? Take a look here.
University of Amsterdam
With over 6,000 employees, 30,000 students and a budget of more than 600 million euros, the University of Amsterdam (UvA) is an intellectual hub within the Netherlands. Teaching and research at the UvA are conducted within seven faculties: Humanities, Social and Behavioural Sciences, Economics and Business, Law, Science, Medicine and Dentistry. Housed on four city campuses in or near the heart of Amsterdam, where disciplines come together and interact, the faculties have close links with thousands of researchers and hundreds of institutions at home and abroad.
The UvA’s students and employees are independent thinkers, competent rebels who dare to question dogmas and aren’t satisfied with easy answers and standard solutions. To work at the UvA is to work in an independent, creative, innovative and international climate characterised by an open atmosphere and a genuine engagement with the city of Amsterdam and society.
Faculty of Science – Informatics Institute
The Computational Science Lab (CSL) at the Informatics Institute of the Faculty of Science tries to understand how information is processed in natural settings through the study of a large variety of dynamic multi-scale complex systems. With a common denominator in computational science and complex systems science, CSL aims at innovating methodologically and theoretically as well as reaching impact in a wide range of application domains.
This PhD position is part of a ZonMw project. In terms of embedding, you will work part-time at the Institute for Advanced Study (IAS) of the University of Amsterdam (UvA) and part-time in CSL. You will become connected through nation-wide societies such as the Dutch NetSci chapter, the Netherlands Platform of Complex Systems, and the Dutch Institute of Emergent Phenomena. You will join an interdisciplinary team, consisting of researchers from the Computational Science Lab (CSL), the Radboud Alzheimer Center, collaborators across the Netherlands in various settings, and even collaborators across various countries in a complementary EU project which you will interact with.
The Faculty of Science has a student body of around 7,000, as well as 1,600 members of staff working in education, research or support services. Researchers and students at the Faculty of Science are fascinated by every aspect of how the world works, be it elementary particles, the birth of the universe or the functioning of the brain.
The mission of the Informatics Institute is to perform curiosity-driven and use-inspired fundamental research in Computer Science. The main research themes are Artificial Intelligence, Computational Science and Systems and Network Engineering. Our research involves complex information systems at large, with a focus on collaborative, data driven, computational and intelligent systems, all with a strong interactive component.
Do you have questions about this vacancy? Or do you want to know more about our organisation? Please contact:
- Dr. Rick Quax, Assistant Professor