Author: Maxime Sangnier

A fully funded 3.5-year PhD studentship in NLP on the topic of meaning
change is offered at Queen Mary University of London (QMUL), School of
Electronic Engineering and Computer Science.
 
I am looking for brilliant candidates who hold (or about to hold) MSc in
Computer Science with a strong NLP research background. Prospective
students can learn more about the project here
<http://eecs.qmul.ac.uk/phd/phd-studentships/principal-and-epsrc-dtp-phd-studentships-in-electronic-engineering-and-computer-science/>,
under the section: *Next generation NLP methods for meaning change* . The
PhD student will be supervised by me and co-supervised by Prof Maria
Liakata, and will also be part of the Change is Key!
<https://www.changeiskey.org/> international research program.
 
For further details on the application process and eligibility criteria
please read this
<http://eecs.qmul.ac.uk/phd/phd-studentships/principal-and-epsrc-dtp-phd-studentships-in-electronic-engineering-and-computer-science/>
.
 
If you are interested, please get in touch with me on:
h.dubossarsky@qmul.ac.uk.

Jonas Martin Peters <jonas.peters@math.ku.dk>: Dec 14 01:52PM

Dear all,

There is a PhD position available at ETH Zurich in the area of causal inference and distribution generalization with possible applications in Earth system science (starting date: April 1st 2023 or after) with me as supervisor. If you are interested, please send me an email with subject line “application PhD position” by Dec 20, 23:59 (anywhere on Earth). Please include
* your CV
* transcripts (such as courses and grades during your BSc and MSc degree)
* research statement (this should contain a short motivation for applying for this position)
* a scientific text written primarily by you (this can be a master thesis, for example, or a research paper if you are first author).

A fully funded 4-year PhD position at the intersection of NLP and Topology
is offered at Queen Mary University of London (QMUL), School of Electronic
Engineering and Computer Science. It is part of the collaboration scheme
between QMUL and the China Scholarship Council (CSC), and is therefore
available for Chinese candidates only.
 
The CSC scheme provides full tuition fee waiver and living stipend for 4
years, and requires (among other things) an English Language test (IELTS)
from the last 2 years. You can read more about the scheme’s requirements
here
<https://www.qmul.ac.uk/scholarships/items/china-scholarship-council-scholarships.html>
.
 
I am looking for brilliant candidates who hold (or about to hold) MSc in
Computer Science with a strong NLP research background. Prospective
students can learn more about the project here
<http://eecs.qmul.ac.uk/phd/phd-studentships/csc-phd-studentships-in-electronic-engineering-and-computer-science/>,
under the section: *Understanding neural representations via their
algebraic-topological structures*. The PhD student will work in an
interdisciplinary environment, and will be at the forefront of NLP
research. If you are interested, please get in touch with me on:
h.dubossarsky@qmul.ac.uk.

Simula Research Laboratory (https://www.simula.no/) is seeking one
three-year full time paid PhD researcher position on data-driven
testing of autonomous agents in the Department of Validation
Intelligence for Autonomous Software Systems. The position is located
in Oslo, Norway.
 
This PhD project explores the combined, hybridized application of
logic-based and data-driven methods for the validation of autonomous
agents, such as collaborative or mobile robots, autonomous cars, or,
more generally, adaptive software systems. These agents need to be
reactive in a fail-safe and secure way to avoid harming humans or
causing security issues. Expected reactions are encoded in the
(high-level and abstract) security specification of the agent, either
given by domain experts or learned during construction/training.
 
The project will develop methods to construct test scenarios from a
specification. Diverse variations of these scenarios will validate the
agent’s resilience and functionality, including functional, i.e. the
correct execution of given tasks, and non-functional requirements,
such as security requirements or performance.
 
As the technological basis, we will combine and exploit techniques
from 1) software testing, including metamorphic and constraint-based
testing, and 2) artificial intelligence, including logic-based
constraint satisfaction, and data-driven machine learning, e.g.
generative adversarial networks for input synthesis and reinforcement
learning for scenario control.
 
The appointment starts after or in March 2023, with some flexibility.
The review of candidates will be performed continuously until the
position has been filled.
 
Read more: https://www.simula.no/about/job/call-phd-student-data-driven-testing-autonomous-agents
 

We are looking for an excellent, creative, and highly motivated scientist
with a MSc or equivalent in computer science, network science, statistical
physics, applied mathematics, data science, computational social science or
related fields. The candidate is going to work in the data analysis of
multi-attributed online social networks for understanding the emergence of
intersectional inequalities and biases in network-based algorithms. The
project is funded by a EU Horizon Europe grant (Multi-Attribute, Multimodal
Bias Mitigation in AI Systems, Grant ID: 101070285) and implemented in
close collaboration with other research organizations that are aiming for
socially responsible AI solutions.

This is a 3-year PhD position to work with Fariba Karimi [1] in the
Computational Social Science and Network Inequality team at the Complexity
Science Hub Vienna, Austria [2]. The successful candidate will play a
leading role within this funded project, designing, managing, executing,
and publishing research in collaboration with other researchers within this
project and elsewhere. You will work in close collaboration with network
scientists, physicists, computer scientists, and social scientists to
analyze multi-criteria fairness in network-based algorithms and to develop
intervention and mitigation methods.

Please send your application material to applications@csh.ac.at with the
subject line “PhD Fairness in Networks”. The application must include:

1. a curriculum vitae
2. a list of publications
3. a brief research statement (why you think you are an excellent
candidate in this topic and what research you would like to do with us)
4. any additional material that helps us to understand that you are
research-oriented, technically skilled, and creative
5. names and full contact addresses of at least two individuals who are
willing to write a letter of recommendation for you if we request it.

We will start evaluating applications immediately. The call remains open
until the position is filled. CSH is committed to the principle of equal
employment opportunity for all applicants. All employment decisions are
therefore based on job requirements, qualifications, merit, and
organizational needs. We strongly encourage individuals from
underrepresented groups to apply. We process your personal data in
accordance with the law (https://www.csh.ac.at/data-protection/).

More
info: https://www.csh.ac.at/wp-content/uploads/2022/11/CSH_Job_PhD_MULTI_CRITERIA_FAIRNESS_IN_NETWORKS.pdf

Best,
Lisette Espin-Noboa

Research and teaching position (postdoc or PhD student) in computational
linguistics
 
HTML version with hyperlinks:
https://www.coli.uni-saarland.de/~koller/page.php?id=jobs
 
 
We are looking to fill a research and teaching position in computational
linguistics at the Department of Language Science and Technology at
Saarland University. The position is part of the research group of Prof.
Alexander Koller, but offers great flexibility in developing your own
research and teaching agenda, and collaborations with other research groups
are encouraged.
 
The position is flexible with respect to topic, but it should connect
thematically with current topics of interest to the research group. These
include syntactic and semantic parsing, semantics, dialogue, and natural
language generation; themes of particular interest are currently user
adaptation in interactive NLP and neurosymbolic models. You should have
expertise in neural and/or linguistically principled methods in
computational linguistics and be willing to take an active role in shaping
the research and teaching environment of the department.
 
The position includes a teaching load of up to four hours per week in the
BSc Computational Linguistics (in German) and/or the MSc Language Science
and Technology (in English). Both programs attract excellent and highly
motivated students; it is not unusual for our students to publish papers at
peer-reviewed conferences before graduation. The MSc students in particular
are a very international crowd, with two thirds joining us from abroad. You
will typically teach two seminars per semester on topics of your choice,
which will allow you to motivate students to do BSc and MSc theses under
your supervision.
 
This is a position on the German TV-L E13 scale (100% position at the
postdoc level; 75% position at the PhD student level). The starting salary
of a 100% TV-L E13 position is a bit over 50,000 Euros per year and
increases with experience. The initial appointment will be for three years;
the position can be extended up to the limits of the German law for
academic contracts (WissZeitVG). The starting date is April 1 or later: We
want to fill the position in 2023, but could leave it open beyond April for
the ideal candidate.
 
 
Requirements
 
We are looking for candidates who have finished, or are about to complete,
an excellent PhD degree (at the postdoc level) or MSc degree (at the PhD
student level) in computational linguistics, computer science, or a related
discipline. You must be proficient in English (spoken and written); the
ability to teach in German is a plus.
 
Priority will be given to applicants at the postdoc level, who should have
demonstrated their research expertise through high-quality publications.
However, we will also consider applicants at the PhD student level.
 
 
About the department
 
Saarland University is one of the leading centers for computational
linguistics in Europe, and offers a dynamic and stimulating research
environment. The Department of Language Science and Technology consists of
about 100 research staff in nine research groups in the fields of
computational linguistics, psycholinguistics, speech processing, and corpus
linguistics.
 
The department is the centerpiece of the Collaborative Research Center 1102
“Information Density and Linguistic Encoding”. It is part of the Saarland
Informatics Campus, which brings together computer science research at the
university with world-class research institutions on campus, such as the
Max Planck Institute for Informatics, the Max Planck Institute for Software
Systems, and the German Research Center for Artificial Intelligence (DFKI).
The Saarland Informatics Campus brings together 900 researchers and 2100
students from 81 countries; SIC faculty have won 36 ERC grants.
 
Saarland University is located in Saarbrücken, a mid-sized city in the
tri-border area of Germany, France, and Luxembourg. Saarbrücken combines a
lively culture scene with a relaxed atmosphere, and is quite an affordable
place to live in. Our department maintains an international and diverse
work environment. The primary working language is English; learning German
while you are here will make it easier to connect with the local culture,
but is not necessary for your work.
 
 
How to apply
 
Please submit your application at http://apply.coli.uni-saarland.de/ak22.
Preference will be given to applications received by 22 January 2023.
 
Include a single PDF file with the following information:
 
• a statement of research interests that motivates why you are applying
for this position and outlines your research agenda;
• a full CV including your list of publications;
• scans of transcripts and academic degree certificates;
• the names, affiliations, and e-mail addresses of two people who can
provide letters of reference for you.
 
Saarland University especially welcomes applications from women and people
with disabilities.
 
If you have further questions, please email Alexander Koller <
koller@coli.uni-saarland.de>. Applications should _not_ be emailed to this
address, but submitted through the online form.

A fully-funded PhD studentship that covers 3.5 years full international
tuition, stipend of £20,668k per year, a £1k research training support per
year is available for an April or July 2023 PhD start. The studentship is
partly sponsored by National Physics Lab (NPL) in the UK and it will
involve a secondment for at least three months in the Data Science
Department of NPL during the course of the PhD.
 
The topic is on the intersection of machine learning and sequential Monte
Carlo methods and we welcome general interests on statistical machine
learning and computational statistics. We are looking for candidates who
holds a Bachelor’s degree or above in Computer Science, Electrical
Engineering, Statistics, Mathematics, Physics or similar (a First Class or
the equivalent from an overseas university) with a strong research
background on statistical machine learning, deep learning, or computational
statistics.
 
The application is rolling-based and we will fill in the position as soon
as a suitable candidate is identified. If you are interested, please get in
touch with me on yunpe…@surrey.ac.uk <http://yunpeng.li@surrey.ac.uk/> including
copies of your CV and transcripts before you apply for the position.
 
Applications should be submitted via the University of Surrey Computer
Science PhD programme
<https://www.surrey.ac.uk/postgraduate/computer-science-phd>page on the
“Apply” tab. Please clearly state the studentship title “Machine learning
meets sequential Monte Carlo” and supervisors “Dr Yunpeng Li and Prof Wenwu
Wang” on your application.

A fully funded PhD position in *Advanced Deep Data-Driven Nowcasting
Models *is available in our group at Utrecht University, The Netherlands.
(apply before *January 9th, 2023*).
 
The research in this PhD project will be on developing a new theory to
achieve more reliable and accurate nowcasting deep learning models. The key
idea is to leverage large amount of unlabelled data for learning meaningful
representation, incorporating several atmospheric variables and equipping
the models with uncertainty quantification.
 
In this context, we are looking for PhD candidates who have experience in
machine learning, deep learning and have a strong interest in the
developing novel deep learning techniques for weather elements nowcasting.
 
*For more information and guidance on how to apply, see:* PhD position in
Advanced Deep Data-Driven Nowcasting Models
<https://www.uu.nl/en/organisation/working-at-utrecht-university/jobs/phd-position-in-advanced-deep-data-driven-nowcasting-models-10-fte>