provinces" is open at the Alfred Wegener Institute in Bremerhaven:
https://recruitingapp-5442.de.umantis.com/Vacancies/762/Description/2
** Background **
We aim to use machine learning to define biogeochemical and ecological
provinces in the ocean. From this, we expect a fundamental support to
study the impact of global change on the world ocean. After assimilating
a basic data product, an open-access software tool that allows
assessment of the variability of oceanographic core data shall be
developed. The project aims at the following research questions:
* Class assignment and validation *: How do provinces that are assigned
by machine learning compare to the existing concept of ecological
provinces? (Longhurst 2006)
* Key indicators *: given an interdisciplinary and multivariate data
product – what are the main drivers of variability? Is it possible to
establish a small number of basic features for the identification of
provinces (data reduction)?
* Prediction *: Based on a better mechanistic understanding - can we
predict how regional provinces and water masses change as a response to
climatic changes?
** Tasks **
You will:
- carry out extensive data assimilation for global oceanographic and
chemical data
- use machine-learning to assess drivers of variability in the dataset
and to allow predictions
- reduce complexity by developing key sets of features
- develop a user interface that supports sustainable and open-access usage
- publish your results in international peer-reviewed journals.
** Requirements **
- Master's degree in mathematics or computer science
- experience in statistical machine learning
- programming skills in at least one of the languages Python, C++, or Java
- motivation to work with different disciplines of ocean ecology and
marine chemistry.Further Information
For further information,please contact Prof. Dr S. Maneth
(maneth@uni-bremen.de) or Prof. Dr Boris Koch (Boris.Koch@awi.de;
+49(471)4831-1346).
This position is limited to 3 years. The salary will be paid in
accordance with the Collective Agreement for the Public Service of the
Federation (Tarifvertrag des öffentlichen Dienstes, TVöD Bund), up to
salary level 13 (100%). The place of employment will be Bremerhaven.
You will participate in the Helmholtz School for Marine Data Science
MarDATA.
The AWI is characterised by
- our scientific success - excellent research.
- collaboration and cooperation - intra-institute, national and
international, interdisciplinary.
- opportunities to develop – on the job, aiming at other positions and
beyond AWI.
- a culture of reconciling work and family – an audited and
well-supported aspect of our operation
- our outstanding research infrastructure – ships, stations, aircraft,
laboratories and
more.
- an international environment – everyday contacts with people from all
over the world.
- having an influence – fundamental research with social and political
relevance
- flat hierarchies – facilitating freedom and responsibility
- exciting science topics, with opportunities also in technology,
administration and infrastructure
Equal opportunities are an integral part of our personnel policy. The
AWI aims to increase the number of female employees and therefore
strongly encourages qualified women to apply.
Disabled applicants will be given preference when equal qualifications
are present.
The AWI fosters the compatibility of work and family in various ways and
has received a number of awards as a result of this engagement.
We look forward to your application!
Please submit your application, including
(1) a letter of motivation,
(2) two letters of recommendation or the contact information of two
references and
(3) a list of publications,
by February 17th, 2021 exclusively online.
Selected candidates will be invited to present their research ideas and
motivation during the "Annual recruitment days", planned from 01. to 23
April 2021 and expected to be online.
Reference number 21/40/G/MarData-b
Apply here:
https://recruitingapp-5442.de.umantis.com/Vacancies/762/Description/2
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