stillingsbetegnelse:
PhD position in the area of Methods and Tools for the Statistical Data Analysis for Large Datasets collected from Bio-based Manufacturing Processes

jobbeskrivelse:
DTU Compute would like to invite applications for a 3-year PhD position starting June 1 2015 or soonest hereafter.The project is financed jointly by the Danish Research Council through the BioPro2 project and by DTU. Project Description The Statistics and Data Analysis section at DTU Compute is looking for a PhD student in the area of methods and tools for the statistical data analysis for large datasets collected from bio-based manufacturing processes. The project is part of larger project (BioPro2) involving various groups within DTU and KU and collaboration with these groups is expected. Moreover it is also expected the project to involve close collaboration with industry and therefore to involve case studies and real life applications. Extracting useful information from the extensive data collected in bio-based manufacturing is both a practical and an academic challenge. With the proliferation of computer and sensor technology, massive data streams are now being collected and stored waiting to be analyzed. Tools for automatically extracting the useful information from such datasets are urgently needed. The focus of this project is therefore on the statistical analysis in this data rich environment in order to make information hidden in process industry data-streams more easily accessible to the process scientists. Various objectives of the project in general are to develop: 1.Systematic data collection methodologies through controlled experiments for the unit operations as a whole to exploit possible interactions among these operations 2.Effective design and analysis techniques for simulation experiments as well as optimization procedures for the simulation models that will be developed by other groups with BioPro2. 3.Methodologies to support and improve mechanistic process models through empirical data analysis. 4.Methodologies to combine engineering process control (EPC) applications with statistical process control (SPC) to eliminate special causes that generate excessive variation in the processes. 5.Algorithms for detection of specific patterns in the input and output variables. The PhD project is expected to tackle some of these broader objectives for which conventional statistical tools often fall short in delivering the appropriate analysis due to the nature of the data collected in these processes. The data rich environments in which this project will be conducted necessitate genuine scientific contributions rather than mere applications of already existing methods. Research attempts of addressing any of these issues have so far constituted acknowledgment of the data related challenges stemming from the very nature of the batch and fed-batch processes that will be considered in this project. In that regard, the project presents a unique opportunity to perform cutting edge yet practical research in above mentioned objectives. Requirements The PhD candidate must have a master degree in engineering or natural sciences or equivalent academic qualifications. The candidates must have a strong background in statistical analysis, mathematical modelling, and computing. Candidates with practical experience with large datasets and in industrial statistics (i.e. in design of experiments, statistical process control and multivariate statistics) are preferred and highly encouraged to apply. Furthermore knowledge in statistical software packages such as R and JMP is required. The candidate must be fluent in English, in both speaking and writing with great communication and presentation skills. Approval and Enrolment The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in the ITMAN Graduate School Programme of DTU Compute. For information about the general requirements for enrolment and the general planning of the scholarship studies, please see the DTU PhD Guide. Assessment The assessment of the applicants will be made by Associate Professor Murat Kulahci, Associate Professor Lin

Arbejdsgiver Navn: Danmarks Tekniske Universitet

Arbejdsgiver telefonnummer: 45252525

Arbejdsgiver faxnummer: 45881799

Job kort beskrivelse:
Undervisning og forskning på universiteter og højere læreranstalter

land: Danmark

region: Hovedstaden

krævede uddannelse: Ikke angivet

Kilde til jobtilbud: AMS, Offentlige arbejdsformidlinger, Danmark