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<b>Two Wallenberg Artificial Intelligence Program PhD Student
Positions at Umeå University.</b><b><br>
</b><br>
The Department of Computing Science, is seeking outstanding
candidates for two Wallenberg Autonomous Systems Program (WASP) PhD
student positions in Computer Science. Deadline for application is
November 10, 2018.<br>
<br>
<b>Research topic 1: Software Engineering Methods for Responsible
Artificial Intelligence</b><b><br>
</b>URL: <a class="moz-txt-link-freetext"
href="https://umu.varbi.com/what:job/jobID:231010/"
moz-do-not-send="true">https://umu.varbi.com/what:job/jobID:231010/</a>
<br>
Reference number: AN 2.2.1-1620-17<br>
<br>
In order to ensure Responsible Artificial Intelligence applications,
we need to ensure that the development of AI systems is mindful of
the consequences for individuals and societies, by anticipating the
consequences of the design choices, reflect upon the problem being
solved by engaging all stakeholders, and take appropriate action to
ensure social, legal and ethical acceptability of the system.<br>
Therefore, Responsible Design of Intelligent Systems concerns the
methods and tools for design and development that ensure the
analysis and evaluation of ethical, legal and societal implications.<br>
The aim of this project is to develop an engineering process model
by which ethical considerations can be addressed throughout the
various stages of software system development. We will take as
starting point Design for Values approaches and existing methods to
identify and align the possibly conflicting values of all
stakeholders. Application of these conceptual approaches to software
engineering requires formal transformation and verification of
abstract values into concrete software design requirements and
computational functionalities in ways that are transparent, open for
inspection and appropriately describe the chain of stakeholder
involvement and responsibility. This is an important and urgent
research area to make these approaches effective in designing
responsible AI applications.<br>
<br>
<br>
<b>Research topic 2: Verification and control of intelligent
autonomous systems</b><b><br>
</b>URL: <a class="moz-txt-link-freetext"
href="https://umu.varbi.com/en/what:job/jobID:231037/"
moz-do-not-send="true">https://umu.varbi.com/en/what:job/jobID:231037/</a>
<br>
Reference number: AN 2.2.1-1621-18<br>
<br>
AI systems are increasingly expected to act autonomously. Using
current Machine Learning approaches that focus on pattern matching
and rely heavily on correlation methods leads to impenetrable
systems that are notoriously difficult to monitor (the so called
black box algorithms). However, trust on autonomous systems depends
on the possibility to verify and minimally control their behaviour.
In particular, it becomes increasingly important to formally ensure
that the behaviour of an AI system lays within some given
principles.<br>
An urgent research area in AI is therefore the development of
theories and methods for control and verification of autonomous
systems. This requires going beyond traditional control system
methods, for two main reasons. Firstly, an autonomous system will by
definition operate in open environments, which cannot be fully
described nor defined a priori, and therefore rules and constraints
on behaviour will not be able to fully regulate all possible
situations encountered by the system. Secondly, opacity is inherent
in open environments and cannot be avoided, e.g. because the systems
are developed and operated by different entities, with possible
proprietary issues. The control of autonomous systems in open
environments can best be done by compliance regulatory approaches,
which are based on the observation of input and output behaviour
rather than on the regimentation of internal processes. This is in
fact what the legal systems do in the human world.<br>
This research project will explore formal approaches to verification
and control of autonomous systems that take into account the
different values and requirements of stakeholders, the dynamics of
the environment and the inevitability of opaqueness of learning
methods. The resulting solutions will enable monitoring and
regulation of the input and output of an AI system, based on a set
of ethical principles.<br>
<br>
<b>About the Department and the research group</b><b><br>
</b>The Department of Computing Science is a dynamic environment
with around 100 employees representing more than 20 countries
worldwide. We conduct education and research on a broad range of
topics in Computing Science.<br>
<br>
The Social and Ethical Artificial Intelligence group conducts
research into AI systems that meet their social responsibility,
including the development of theories, models and tools for
oversight, accountability and verification, and methods to analyse,
design, measure and audit social implications The group collaborates
with several national and international research groups, and has
active links with industry and policy organisations. Visit <a
class="moz-txt-link-freetext"
href="http://people.cs.umu.se/virginia/for" moz-do-not-send="true">http://people.cs.umu.se/virginia/for</a>
more information.<br>
<br>
<b>WASP program</b><br>
The project is part of the Wallenberg AI, Autonomous Systems and
Software Program (WASP), Sweden’s largest ever individual research
program, and a major national initiative for strategically basic
research, education and faculty recruitment. The program is
initiated and generously funded by the Knut and Alice Wallenberg
Foundation (KAW) with 2.6 billion SEK. In addition to this, the
program receives support from collaborating industry and from
participating universities to form a total budget of 3.5 billion
SEK. Major goals are more than 50 new professors and more than 300
new PhDs within AI, Autonomous Systems and Software. The vision of
WASP is excellent research and competence in artificial
intelligence, autonomous systems and software for the benefit of
Swedish industry. For more information about the research and other
activities conducted within WASP please visit <a
class="moz-txt-link-freetext" href="http://wasp-sweden.org/"
moz-do-not-send="true">http://wasp-sweden.org/</a>.<br>
<br>
The graduate school within WASP provides foundations, perspectives,
and state-of-the-art knowledge in the different disciplines taught
by leading researchers in the field. Through an ambitious program
with research visits, partner universities, and visiting lecturers,
the graduate school actively supports forming a strong
multi-disciplinary and international professional network between
PhD students, researchers and industry. It thus provides added value
on top of the existing PhD programs at the partner universities,
providing unique opportunities for students who are dedicated to
achieving international research excellence with industrial
relevance<br>
<br>
<b>About the positions</b><br>
The successful applicant will be employed by Umeå University and
receive a competitive salary for a period of four years of full time
PhD studies, provided that the studies are progressing reasonably
well. PhD students are typically offered the opportunity to gain
teaching experience on suitable undergraduate courses. If so, the
employment period is extended to cover the time spent on teaching
(at most 20 %).. Expected starting date is 1st of January 2019 or as
otherwise agreed.<br>
<br>
<b>Admission requirements</b><br>
The applicant is required to have completed a second- cycle level
degree, or completed course requirements of at least 240 ECTS
credits, of which at least 60 ECTS credits are at second-cycle
level, or have an equivalent education from overseas, or equivalent
qualifications. To fulfil the specific entry requirements for
doctoral studies in computing science, the applicant is required to
have completed courses at second-cycle level degree equivalent to 60
ECTS credits in computing science, or in a subject considered to be
directly relevant for the specialisation in question.<br>
<br>
Candidates are expected to have very good knowledge in Artificial
Intelligence and software engineering. Demonstrable knowledge of
systems design and modelling, multi-agent systems, or software
development is a pre. In particular, candidates should be well
acquainted with relevant engineering and algorithmic techniques
which will be applied to develop design methodologies that account
for social and ethical aspects of AI and ensuring Responsible design
and development.<br>
<br>
Since research is conducted in an international research
environment, the ability to collaborate and contribute to teamwork,
and a very good command of the English language, both written and
spoken, are key requirements.<br>
<br>
<br>
<b>Application</b><br>
<p>A complete application should contain the following documents:</p>
<ul>
<li> A cover letter including a description of your research
interests, your reasons to apply for the position, and your
contact information</li>
<li>A curriculum vitae</li>
<li>If applicable, copy of completed BSc and/or MSc thesis and
other original research publications</li>
<li>Copies of degree certificates, including documentation of
completed academic courses and obtained grades</li>
<li>Contact information for two persons willing to act as
references</li>
</ul>
The application must be written in English or Swedish, and attached
documents must be written in or translated to English or Swedish.
Documents must be in Word or pdf format. Applications must be
submitted electronically using the e-recruitment system of Umeå
University, and be received no later than November 10, 2018.
Indicating the respective reference number.<br>
<br>
The procedure for recruitment for the position is in accordance with
the Higher Education Ordinance (chapter 12, 2§) and the decision
regarding the position cannot be appealed. The recruitment aims at a
balanced gender distribution, and in particular women are encouraged
to apply.<br>
<br>
For additional information, please contact Virginia Dignum <a
class="moz-txt-link-abbreviated" href="mailto:virginia@cs.umu.se"
moz-do-not-send="true">virginia@cs.umu.se</a> .<br>
<br>
We look forward to receiving your application!<br>
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