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PhD Project in the research field of Marine Dynamics

Position
PhD Project in the research field of Marine Dynamics

Employer
Tallinn University of Technology logo

Tallinn University of Technology

Tallinn University of Technology (TalTech) is the flagship of Estonian engineering and technology education. TalTech is Estonia’s most innovative university, as confirmed by the Estonian universities’ reputation survey. TalTech is especially known for its innovation in the field of digital technologies and engineering. The amount of full-time students exceeds 11,000 (incl. 1600 students international degree students) from 94 different countries and over 1,800 employees from 51 different countries.
Founded in 1918, TalTech is located in Tallinn, the capital of Estonia. TalTech is ranked 601-650 in the QS World University Rankings with subfields such as Engineering and Technology, and Business Administration ranked 451-500. At TalTech, creative technologies are developed, such as self-driving cars or the TTÜ100 satellite. We offer an opportunity to study in a modern digital campus where many of the most recent technologies are tested and implemented on the daily basis.
For more details see https://www.ttu.ee/?id=94518

Homepage: https://www.taltech.ee/university/ttu-in-brief/


Location
Tallinn, Estonia

Sector
Academic

Relevant divisions
Earth and Space Science Informatics (ESSI)
Geodesy (G)
Ocean Sciences (OS)

Type
Full time

Level
Student / Graduate / Internship

Salary
Tuition fee is waived for all PhD students. All PhD students studying with full-load have the right to receive doctoral allowance (660 €) paid by the government. The research group provides the remaining salary.

Required education
Master

Application deadline
21 June 2019

Posted
7 April 2019

Job description

Title of doctoral thesis topic: Identification and improved modelling of marine dynamics by utilizing the Marine Geoid

Background: Hydrodynamic models are often used to simulate water levels, currents, sediment transport and chemical properties (e.g. salinity, temperature, etc.) of marine environment. Thus they are quite effective in understanding and predicting trends and persistent dynamical features in the marine area. In many circumstances however, the accuracy and representation of the dynamical characteristics especially on the (sub)mesoscale have not been adequate enough for various reasons (e.g. parameterization used, model resolution, forcing data etc.). This often results in the under- or overestimated of marine dynamics, that in effect has drastic consequences for engineering, shipping and scientific applications.
This study now proposes a unique methodology that shall improve the accuracy and representation of oceanographic dynamics by utilizing the data assimilation of hydrodynamic and geoid model along with space-borne and in-situ (laser scanning, tide gauges, etc.). The basic concept stems from utilization of a geoid model. Recalling that the geoid represents the equipotential surface (i.e. it defines sea level shape that the ocean surface would take under the influence of the gravity and rotation of Earth alone). In reality however the ocean is influenced by other influences such as winds, tides etc. which is often captured by hydrodynamic models and in situ data with respect to their sea surface heights (SSH). Thus it is expected that due to dynamic processes present in the ocean and atmosphere, the SSH are expected to depart from the geoid. This separation is known as the ocean’s dynamic topography (SSH-geoid=DT). DT represents the mean and time varying currents. Thus intuitively, by including SSH (determined from satellite or airborne laser scanning (ALS) missions) in conjunction with DT estimates (e.g. HDMs and in-situ measurements) we can validate and iteratively improve hydrodynamic and marine geoid models. Examining the abnormalities between the models and reference data allows possible identification of marine dynamical features. As a result creative methods can be developed for adjusting the hydrodynamic models.

Tasks: The PhD candidate shall develop a methodology that utilizes a synergy of hydrodynamic and geoid modelling complemented by in-situ data (tide gauges, satellite altimetry etc), to obtain accurate and reliable SSH results and marine geoid model. The first stage of this project requires compilation and statistical analyses of all relevant data whereby the candidate is expected to refer these to a common reference datum, correcting the temporal/spatial mismatch between data sets, performance of statistical analysis between different data sets. The second stage requires detailed understanding on the operations of the hydrodynamic model to be used. This phase essentially involves a statistical approach to data assimilation (training shall be provided), whereby all the in-situ data are combined with the HDM to improve the model. An iterative approach is employed, whereby once results (SSH and inversely geoidal heights) are calculated, they are checked for accuracy and reliability. Inter-comparisons of the two reference models (geoid and SSH) are conducted for detecting abnormalities. Identifying reasons for the detected discrepancies enables to determine whether these are due to poor hydrodynamic representation or/and geoid model errors. Both models can be improved iteratively, e.g. by acquiring new data over suspicious areas and iterative modelling. The candidate is expected to assist in project related field campaigns. This study is part of the Estonian Research Council supported research for developing an iterative approach for near-coast marine geoid modelling by using re-tracked satellite altimetry, in-situ and modelled data.

Qualifications:
The applicants should fulfil the following requirements:
University degree (M.Sc.) in geodesy, geomatics oceanography and other earth sciences. Consideration will also be given to applicants whose previous degrees are in appropriate related disciplines, such as Mathematics, Physics or Software Engineering.
Skills in data analysis, mathematics and statistical analyses (to be trained) and model development (to be trained)
Ability for independent research as part of a team, interest in the presentation and publication of scientific results.
Advanced computer literacy and programming skills.
Good command of the English language (speaking and writing).

The PhD candidate is expected to be at full time position for a duration of 4 years. The candidate is obligated to participate and fulfil the requirements of Tallinn University of Technology PhD programme. Additional funds will be provided (and whence applicable the associated funding can be applied for) for research trainings, conferences and international mobility/stays abroad with durations of up to 6 months.

For inquiries regarding the position and more information consult the project website http://gece.ttu.ee/~geoid/ and e-mail addresses therein.


How to apply

The documents required for application are the following:
1) an application
2) a curriculum vitae incl. data on education as well as research and development activities;
3) an original and a copy of an education certificate and the diploma supplement;
In case an education certificate acquired in a foreign country, TalTech has the right to request an assessment and recommendation from the Estonian ENIC/NARIC Centre or submit the relevant information request to verify the data
4) a copy of the passport, an identity card or a residence permit card;
5) a motivation letter in English.
Application documents can be submitted through the admission system https://estonia.dreamapply.com/
For the details of application procedure please consult https://www.ttu.ee/studying/phd-studies/admission-4/