PhD Topic: Smart Computational Tool for Planing Hull Design based on Intelligent Machine Learning
Description: Artificial Intelligence is one of the most enabling technologies of digital transformation in the industry. The methods and processes that are carried out in Marine Technology cannot be left out of intelligent machine learning. There are many aspects in which Artificial Intelligence (AI) can be applied in ship design because of its direct impact on generating added value, saving time, decreasing the costs and obtaining a more competitive product. The first stage of the lifecycle of high-speed craft (HSC) is designing and the main design aspect of such craft is directly related to their hydrodynamics behaviour including resistance, seakeeping and manoeuvring motions. Therefore, the current thesis aims to develop a computational tool based on the intelligent machine learning that is able to predict the hydrodynamic performance (resistance, seakeeping and manoeuvring) of a particular kind of high-speed craft. The required dataset for creating the Smart Computational Tool (SCT) should be developed based on the validated mathematical models as well as existing experimental data. Moreover, the Genetic Algorithm is another methodology that should be considered in SCT to enable the user to find the optimized solution by considering various constraints and objectives including fuel efficiency. SCT has to be developed in an open source framework in which everyone can extend its functions and capabilities.
The applicants should fulfill the following requirements:
The call is open for candidates with a wide range of backgrounds inside and outside of Estonia. Most importantly, a high level of interest and motivation towards, and deep understanding on, artificial intelligence, machine learning, genetic algorithm and marine technology. A suitable background may come from naval architecture, information technology, computer engineering and mechanical engineering or related disciplines. Prior experience on developing open-source software is a significant advantage and skills with programming tools such as Matlab, Python and C++ is necessary. The candidate should prove his/her capabilities in writing the technical report and scientific papers in high-quality journals. Priority will be given to those who got the first-class honours for his/her bachelor degree and master by coursework course with research components and/or publications. Experience in collaborative research/publication with the exist-ing TalTech staff is also a plus. The applicant for the position must have a Master’s degree and must fulfill the requirements for doctoral students at the Tallinn University of Technology (https://www.ttu.ee/studying/phd-studies/admission-4/).
Closing Date and Start Date:
Deadline for this application is 31/05/2020 (applicants outside EU) and 01/07/2020 (from EU). The work contract is made starting from September 2020.
The position is at the Etonian Maritime Academy of Tallinn University of Technology and may include some work as a teaching assistant in our courses. The expected duration of doctoral studies is four years, but a contract is first made for one year, and the extension is subject to advance of studies and research. The salary is according to the salary system of Tallinn University of Technology.
How to apply for a doctoral candidate position
The application material includes:
1.Motivation letter (maximum one A4 page, important: provide clear, but honest, evidence of your skills related to the job description and requirements above)
2.CV and other proof of scientific activity (publications, conference papers etc.)
3.A certified copy of master´s degree certificate and official transcript of records, and their translations, if the originals are not in English. In the first stage, an unofficial document may also be accepted.
4.An English abstract or summary the MSc thesis.
5.Introducing two referees who can be contacted, directly.
6.Proof of proficiency in English
All material should be submitted in English.
Applications with attachments (in pdf-format) are to be sent to email@example.com no later than 31/05/2020. The position will be fulfilled as soon as a suitable candidate is found.
For additional information, please contact Assistant Professor Abbas Dashtimanesh (email: firstname.lastname@example.org).
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