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PhD within Aquaculture technology –a NTNU-SINTEF-cooperation

Common information
Aquaculture technology is a key competence area today and in the future for developing one of Norway’s most important industrial sectors. Aquaculture technology is a field that provides applied and theoretical scientific challenges of high complexity that can only be solved through interdisciplinary approaches. The Department of Engineering Cybernetics, NTNU and the Department of Seafood Technology at SINTEF Ocean have had a long tradition for collaboration within aquaculture technology research and are therefore currently establishing a co-funded PhD-research group in this area. The group will be formed around a core of three PhD students which positions are recently announced but will also associate with PhDs and PostDocs that are working with aquaculture technology in existing and upcoming research projects. The three announced positions cover several different topics within the scientific field of cybernetics but are all related to specific common challenges the industry faces. It is intended that the research group will become a collective dynamic force for a growing environment in the field of Aquaculture technology while supporting and further strengthening the collaborative bonds between NTNU and SINTEF in this area.
Position 1: Autonomous vessels for controlled Fish-Machine-interaction (link to announcement at Jobbnorge)
The PhD position is associated with a highly interdisciplinary project at SINTEF (see RACE Fish Machine interaction), which started in June 2020 and targets fundamental research questions in the fields of Biology and Technology interaction, underwater robotics, modelling and control theory. Supervision will be provided through Associate Professor Martin Føre (main academic supervisor) from NTNU and Dr. Eleni Kelasidi (scientific supervisor), leader of the 'RACE Fish-Machine Interaction' project, from SINTEF Ocean. The project will be integrated in the existing and future SFF (e.g. CoE NTNU AMOS) and SFI (e.g. EXPOSED) and will build on and strengthen the established cooperation in biology, marine robotics and autonomy with NTNU and SINTEF partners such as Equinor, SalMar, ScaleAQ, Eelume, WaterLinked and DNV GL. The main workplaces will be the Departments of Engineering Cybernetics at the Norwegian University of Science and Technology (NTNU) and Seafood Technology Department at SINTEF Ocean in Trondheim, and the candidate will have an office space at both locations.
Main duties and responsibilities
The candidate will be expected to contribute to expanding the world of science in areas relevant for achieving the project objectives of RACE Fish Machine interaction. These may include:
  • Developing advanced mathematical models representing the operational environment, including fish behaviour, structural deformations and disturbances, and mathematical models of underwater vehicles designed for operating in dynamically changing environments, accounting for hydrodynamics, locomotion, actuation and sensor data. In particular, this will entail:
    • Integrating existing and new models into a virtual simulation environment featuring moving fish, flexible structures, a variable environment and Remotely Operated Vehicles (ROV).
    • Developing observers that enable fusing numerical models with real-time data.
    • Developing and validating models of underwater vehicles in a flexible and variable environment by integrating environmental sensors data from full-scale data.
  • Developing intelligent bio-interactive control strategies for autonomous operations that focus on environment adaptation and energy efficiency, while minimising the impact on the fish. In particular, this will entail:
    • Developing path planning and path following control concepts for autonomous navigation of ROV in fish cages that account for behaviour change of fish.
    • Developing control strategies that account for flexible structures and variable environmental conditions.
    • Developing advanced bio-interactive control strategies for minimising effects of robotic system on the fish.
    • Developing control approaches for conducting autonomous operations in the presence of fish and flexible structures.
  • Experimentally investigating, demonstrate and showcase the control approaches in laboratory and field studies using underwater vehicles.
  • Disseminating results of the work via conference presentations and peer-reviewed conference and journal publication. Examples of aimed relevant publication channels are ICRA, IROS, CDC, ACC, IJRR, IEEE RAM and IEEE Transaction on Robotics.
  • Verify the outputs from algorithms using video footage of the fish and manual assessment of tail beat rates
  • Collaborating effectively with researchers and students at NTNU and SINTEF Ocean.
Expectations of the position
We expect the candidate to:
  • Commit adequate time and effort to the project;
  • display initiative in identifying and resolving problems relating to the research;
  • manage the work efficiently so as not to place unreasonable demands on supervisors;
  • be well organised and capable of setting and meeting deadlines for various phases of the research;
  • acquire any new skills required as part of the project;
  • maintain frequent and regular contacts with the supervisors;
  • seek and accept in good faith advice from supervisors and advisory panels;
  • fulfil tasks required by the supervisors as part of the project;
  • meet the normal scholarly and professional standards required by the discipline;
  • ensure that all written work is of a high standard of expression and organization;
  • report the results through both written work (especially scientific papers) and oral presentations (specially seminars to various audiences).
There exists the possibility for participating to departmental duties, such as teaching assistance; these shall be negotiated during the job interview.
Position 2: Modelling, simulation and digital twins of bio-technological systems (link to announcement at Jobbnorge)
The PhD position is associated with a highly interdisciplinary project at SINTEF (see RACE Digital cage), which started in June 2020 and aspires to develop a digital platform for monitoring and visualising aquaculture net cages. Real-time monitoring and modelling of the biological systems and processes in fish farms are core elements in aquaculture cybernetics. Fish can be monitored during production using technologies ranging from telemetry where the fish are equipped with sensors providing individual-based data to cameras based and hydroacoustic devices (e.g. echo sounders, sonars) providing data on a group/population level. Relevant mathematical models for assessing the dynamics in such systems include models of behaviour, energetics and growth, on both individual and group levels. NTNU ITK and SINTEF Ocean currently have collaborative research activities in these fields.

Supervision will be provided through Associate Professor Martin Føre (main academic supervisor) from NTNU and Dr. Biao Su (scientific supervisor), who is central in the 'RACE Digital Cage’ project, from SINTEF Ocean. The project will be integrated in the existing and future SFF (e.g. CoE NTNU AMOS) and SFI (e.g. EXPOSED) and will build on and strengthen the established cooperation in biology, marine robotics and autonomy with NTNU and SINTEF partners such as Equinor, SalMar, ScaleAQ, Eelume, WaterLinked and DNV GL. The main workplaces will be the Departments of Engineering Cybernetics at the Norwegian University of Science and Technology (NTNU) and Seafood Technology Department at SINTEF Ocean in Trondheim, and the candidate will have an office space at both locations.

Main duties and responsibilities
The candidate will be expected to contribute to expanding the world of science in areas relevant for achieving the project objectives of RACE Digital Cage. These may include:
  • Validate and further develop mathematical fish models using data from actual fish farms (e.g. echo sounders, machine vision)
    • Refine and tune existing features in the behaviour model
    • Develop new mathematical representations of response patterns towards environmental conditions
    • Developing and validating models of underwater vehicles in a flexible and variable environment by integrating environmental sensors data from full-scale data.
  • Develop new model modules for simulating e. g. fish stress and fish responses under operational variability such as crowding
    • Participate in experiments to acquire new knowledge on fish responses to features of the cage environment
    • Develop mathematical representations of observed responses
  • Develop data assimilation methods for estimating fish states (behaviour, physiology, stress) in sea-cages by combining mathematical models and real-time sensor systems in estimator structures (e.g. Kalman filters)
    • Acquire an overview of potential data sources and their capabilities/limitations. This will cover sources from manual registrations as well as group based (e.g. echo sounders, cameras) and individual based (e.g. biosensors, telemetry) methods
    • Survey existing data assimilation methods for potential candidates that fit the properties of both the fish model and identified data sources
    • Develop framework based on selected data sources and assimilation methods
  • Disseminate results through peer-reviewed conferences/journals
  • Collaborate with students/researchers at NTNU/SINTEF
Expectations of the position
We expect the candidate to:
  • Commit adequate time and effort to the project;
  • display initiative in identifying and resolving problems relating to the research;
  • manage the work efficiently so as not to place unreasonable demands on supervisors;
  • be well organised and capable of setting and meeting deadlines for various phases of the research;
  • acquire any new skills required as part of the project;
  • maintain frequent and regular contacts with the supervisors;
  • seek and accept in good faith advice from supervisors and advisory panels;
  • fulfil tasks required by the supervisors as part of the project;
  • meet the normal scholarly and professional standards required by the discipline;
  • ensure that all written work is of a high standard of expression and organization;
  • report the results through both written work (especially scientific papers) and oral presentations (specially seminars to various audiences).
There exists the possibility for participating to departmental duties, such as teaching assistance; these shall be negotiated during the job interview.
Position 3: Artificial intelligence and computer vision for applications in Fish Welfare monitoring (link to announcement at Jobbnorge)
The PhD position is associated to the SINTEF ACE project "RACE WELFARE", which started in June 2020. The aim of this project is to assess how and to what extent the environmental parameters and location/layout of the salmon cages affect the welfare (behaviour, growth) and the health of the fish. The secondary objectives are:
  • Map the fish welfare at cage level in farms.
  • Map the variation of environmental parameters within the farms.
  • Map the difference in behaviour of salmon from the same group in a farm but in different cages.
This project will develop fundamental knowledge of production environments, fish behaviour, welfare and health in farming systems (skirt and without skirt) and locations using two case studies (exposed, open sea). The project will also provide knowledge about optimal farm layout for avoiding/reduce health diseases and/or increase welfare.

Supervision will be provided through Associate Professor Annette Stahl (main academic supervisor) from NTNU and a scientific supervisor from SINTEF Ocean. The project will be integrated in the existing and future SFF (e.g. CoE NTNU AMOS) and SFI (e.g. EXPOSED) and will build on and strengthen the established cooperation in biology, marine robotics and autonomy with NTNU and SINTEF partners such as Equinor, SalMar, ScaleAQ, Eelume, WaterLinked and DNV GL. The main workplaces will be the Departments of Engineering Cybernetics at the Norwegian University of Science and Technology (NTNU) and Seafood Technology Department at SINTEF Ocean in Trondheim, and the candidate will have an office space at both locations.

Main duties and responsibilities
It is anticipated that the candidate will contribute to achieving the goals of RACE WELFARE. This may include:
  • Develop mathematical or numerical dynamic models of the fish that mirror the apparent/measured motion of swimming fish
    • Model(s) should capture movements/motions observed for fish kept in flexible sea-cages
  • Fit the model parameters to observed states to determine and classify the underlying fish behaviour
    • Identify behavioural responses of particular interest and data sources/datasets that enables the observation of these
    • Find model parameters that enable the model to reproduce observations
    • Use model to map known health indicators to certain or uncommon behaviour changes that are observed by the available sensors and cameras
  • Use mathematical optimization to determine how a measure of the true fish distribution (ground truth) can be obtained using multiple cameras
  • Develop Machine Learning and Computer Vision based analysis to understand the swarm behaviour of the fish based on video streams
  • Disseminate results through peer-reviewed conferences/journals
  • Collaborate with students/researchers at NTNU/SINTEF
Expectations of the position
We expect the candidate to:
  • Commit adequate time and effort to the project;
  • display initiative in identifying and resolving problems relating to the research;
  • manage the work efficiently so as not to place unreasonable demands on supervisors;
  • be well organised and capable of setting and meeting deadlines for various phases of the research;
  • acquire any new skills required as part of the project;
  • maintain frequent and regular contacts with the supervisors;
  • seek and accept in good faith advice from supervisors and advisory panels;
  • fulfil tasks required by the supervisors as part of the project;
  • meet the normal scholarly and professional standards required by the discipline;
  • ensure that all written work is of a high standard of expression and organization;
  • report the results through both written work (especially scientific papers) and oral presentations (specially seminars to various audiences).
There exists the possibility for participating to departmental duties, such as teaching assistance; these shall be negotiated during the job interview.