PhD position in big data analytics to support ecosystem-based risk management of marine ecosystems- Deadline 26 October 2021

Project description

Marine ecosystems are complex adaptive systems consisting of large networks regulated by the adaptive dynamics of their constituents. Interactions in the networks occur across different levels of ecological organizations (from individual, to population and communities), and are both directly and indirectly modified by environmental pressures. Spatial and temporal dynamics on all levels of ecological organization are emergent properties of these interactions and regulated by local environment conditions. These complex dynamics and structures are central to life on Earth, and are generally investigated using both direct observations and mechanistic modelling of selected biological and physical quantities. However, it remains of critical importance to identify and characterise the relevant scales of ecosystem interactions, the responses of those to pressures and provide indicators of ecosystem state including them in a coherent framework for risk assessment in support of resource management.

In the current PhD project, we plan to develop statistical frameworks based on machine learning approaches (e.g. deep-learning, Bayesian non-parametric models, reinforcement learning) to combine observations and data from general ocean models to:

• Develop adaptive statistical models of marine ecosystems able to combine deterministic and stochastic temporal representations;
• Identify and predict the spatio-temporal dependencies across specific ocean regions;
• Assess the role of resilience for ecosystem dynamics;
• Detect anomalies in very large spatio-temporal datasets of ecosystem state;
• Determine the importance of uncertainties in data input and prediction of ecosystem dynamics;
• Advance decision support tools for risk and vulnerability management in marine ecosystems.

Candidates for the PhD position 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.

We are looking for candidates with:

• An excellent background knowledge and experience in handling and analysing large data (e.g. satellite and in-situ observations)
• Proven skills on advanced statistical modeling
• Ability to develop the project across disciplines (e.g. data science, marine ecology, oceanography, mathematics, etc.)
• Flexibility concerning research stays abroad
• Good communication skills in English, both written and orally
• Ability to conduct research independently and problem solving skills
• Strong interest in participating in an inter-disciplinary and international research environment
• Willingness to contribute to a positive and inspirational work atmosphere

Approval and Enrolment

The scholarship for the PhD degree is subject to academic approval, and the successful candidate is enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see the DTU PhD Guide.

We offer

Application

Please submit your online application no later than 26October 2021 (Danish 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)
• A description of proposed research (max. 2 pages)
• 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)
• Recommendation letters from senior professionals are welcomed

You may apply prior to ob­tai­ning your master’s degree but cannot begin before having received it.

Further information