Boolean networks (BN) are a graph-based well-established method to model biological systems. In order to accurately model systems, we often face models too complex to be interpreted or analyzed. Several reduction techniques exist to mitigate this problem. Our crucial hypothesis is that novel approaches to the reduction of BNs are needed, and that those can be developed by using a theoretical computer science approach. The project aims at developing novel mathematically-grounded techniques and tools to reduce and simplify complex BNs. The starting point will the recent work presented in
Candidates should have a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree. The master degree should be in computational science and engineering (CSE), applied mathematics, or engineering, or equivalent academic qualifications; Preference will be given to candidates who can document experience in formal methods or in analysis of networks, while a documented solid background in discrete math and interest in biological topics will be positively considered. Furthermore, good command of the English language is essential
PhD Project in Computer Science on Techniques and Tools for the Reduction of Biological Systems DTU Compute Share on Facebook Share on Twitter Share on Linkedin Tuesday 08 Oct 19 Apply for this job Apply no later than 31 October 2019 Apply for the job at DTU Compute by completing the following form. Apply online DTU Compute’s Section for Formal Methods invites applications for a 3-year PhD position starting in late 2019 or early 2020. The project is financed by DFF, the Independent Research Fund of Denmark, through the Project ‘REDUCTO: A novel approach for the reduction of Boolean networks’. The PhD student will work under the supervision of the Principal Investigator (PI) of the project and in collaboration with Luca Cardelli (University of Oxford, UK), Claudine Chaouiya (I2M, Aix Marseille Univ, CNRS, Centrale Marseille, Marseille, France & Instituto Gulbenkian de Ciência, Portugal), and Lars Keld Nielsen (Novo Nordisk Foundation Center for Biosustainability, Denmark). Funds are allocated for research visits to the project collaborators. The PhD student will be co-supervised by Andrea Vandin and Alberto Lluch Lafuente. Society is increasingly becoming dependent on the IT infrastructure and is moving towards partly autonomous systems. These systems are exposed to ever growing threats from hackers on top of the traditional vulnerabilities due to shortcomings in the software development process. In the section for Formal Methods we develop tool-supported formal methods for the construction of safe and secure systems, and we also explore some of the newer computational paradigms, including the biologically-inspired ones. The mission is to achieve safety and security by design , so as to ensure that the qualitative and quantitative vulnerabilities of systems can be correctly assessed before being deployed. Project Description Boolean networks (BN) are a graph-based well-established method to model biological systems. In order to accurately model systems, we often face models too complex to be interpreted or analyzed. Several reduction techniques exist to mitigate this problem. Our crucial hypothesis is that novel approaches to the reduction of BNs are needed, and that those can be developed by using a theoretical computer science approach. The project aims at developing novel mathematically-grounded techniques and tools to reduce and simplify complex BNs. The starting point will the recent work presented in Maximal aggregation of polynomial dynamical systems, L Cardelli, M Tribastone, M Tschaikowski, A Vandin, Proceedings of the National Academy of Sciences 114 (38), 10029-10034, https://doi.org/10.1073/pnas.1702697114 Symbolic computation of differential equivalences, L Cardelli, M Tribastone, M Tschaikowski, A Vandin, Proceedings of POPL 2016, https://doi.org/10.1145/2837614.2837649 Tool support will be based on the tool ERODE ( http://bit.ly/ERODE ). Responsibilities and tasks You will be involved in all tasks of the project, under the supervision of the PI and of the project collaborators. In particular: You will learn about BN and related reduction techniques offered by ERODE. You will develop simple case studies to guide the initial developments. After that, you will investigate model repositories to identify complex models from the literature to assess the effectiveness of the developed techniques. You will develop novel reduction techniques for several variants of BNs. Initially you will consider simple variants of BNs for which indirect reduction techniques are already offered by ERODE. Then you will depart from the above listed works to consider BNs variants of increasing complexity. You will instantiate the proposed techniques in a tool and validate them using models identified in the previous points. Starting points will be the tools ERODE ( http://bit.ly/ERODE ) and GinSim ( http://ginsim.org/ ). You will contribute to disseminating the obtained techniques at international conferences and journals. Qualifications Candidates should have a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree. The master degree should be in computational science and engineering (CSE), applied mathematics, or engineering, or equivalent academic qualifications. Preference will be given to candidates who can document experience in formal methods or in analysis of networks, while a documented solid background in discrete math and interest in biological topics will be positively considered. Furthermore, good command of the English language is essential. Approval and Enrolment The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in the DTU Compute PhD School Programme. For information about the general requirements for enrolment and the general planning of the PhD study programme, please see the DTU PhD Guide . Assessment The assessment of the applicants will be made by Associate Professor Andrea Vandin and Head of Section and Associate Professor Alberto Lluch Lafuente. We offer DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility. Salary and appointment terms The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union. The position is a full-time position. The period of employment is 3 years starting 01/01/2020 (or as soon as possible thereafter). You can read more about career paths at DTU here . Further Information Further information concerning the project can be obtained from Andrea Vandin , firstname.lastname@example.org or Alberto Lluch Lafuente , email@example.com . Further information concerning the application is available at the DTU Compute PhD homepage . Application Please submit your online application no later than Thursday, 31 October 2019 (local time) . Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link "Apply online", fill out the online application form, and attach all your materials in English in one PDF file . The file must include: A letter motivating the application (cover letter) Curriculum vitae Grade transcripts and BSc/MSc diploma Excel sheet with translation of grades to the Danish grading system (see guidelines and Excel spreadsheet here ) Candidates may apply prior to obtaining their master's degree, but cannot begin before having received it. Applications and enclosures received after the deadline will not be considered. All interested candidates irrespective of age, gender, race, disability, religion or ethnic background are encouraged to apply. DTU Compute is an internationally unique academic environment spanning the science disciplines mathematics, statistics and computer science. At the same time we are an engineering department covering informatics and communication technologies (ICT) in their broadest sense. Finally, we play a major role in addressing the societal challenges of the digital society where ICT is a part of every industry, service, and human endeavour. DTU Compute has a total staff of 400 including 100 faculty members and 130 Ph.D. students. We offer introductory courses to all engineering programmes at DTU and specialised courses to the mathematics, computer science, and other programmes. We offer continuing education courses and scientific advice within our research disciplines, and provide a portfolio of innovation activities for students and employees. Technology for people DTU develops technology for people. With our international elite research and study programmes, we are helping to create a better world and to solve the global challenges formulated in the UN’s 17 Sustainable Development Goals. Hans Christian Ørsted founded DTU in 1829 with a clear vision to develop and create value using science and engineering to benefit society. That vision lives on today. DTU has 11,500 students and 6,000 employees. We work in an international atmosphere and have an inclusive, evolving, and informal working environment. Our main campus is in Kgs. Lyngby north of Copenhagen and we have campuses in Roskilde and Ballerup.
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