SteelSeries France

The SteelSeries France R&D team (former Nahimic R&D team) is glad to open 4
research internship positions for 2023.

The selected candidates will be working on one of the following topics
(more details in attached):

  • Real time speaker separation
  • Personalized speech enhancement
  • Advanced Selective Mutal Learning for audio source separation
  • Audio detection for gaming

Please reply/apply to nathan.souviraa-labastie@steelseries.com.

SteelSeries is a Danish manufacturer of gaming peripherals and accessories,
including headsets, keyboards, mice, controllers, and mousepads.
SteelSeries was acquired by GN Store Nord in 2021.
Open Roles
 
Machine Learning / Audio Signal Processing Intern
<https://www.karkidi.com/job-details/37356-machine-learning-audio-signal-processing-intern-job>
 
Lille, France
 
Machine Learning / Audio Signal Processing Intern
<https://www.karkidi.com/job-details/37355-machine-learning-audio-signal-processing-intern-job>
 
Lille, France
 
Machine Learning / Audio Signal Processing Intern
<https://www.karkidi.com/job-details/37354-machine-learning-audio-signal-processing-intern-job>
 
Lille, France
 
Machine Learning / Audio Signal Processing Intern
<https://www.karkidi.com/job-details/37353-machine-learning-audio-signal-processing-intern-job>
 
Lille, France

InstaDeep

Jobs at InstaDeep
 
InstaDeep delivers AI-powered decision-making systems for the Enterprise.
With expertise in both machine intelligence research and concrete business
deployments, we provide a competitive advantage to our customers in an
AI-first world. InstaDeep is today an EMEA leader in decision-making AI
products for the Enterprise, with headquarters in London, and offices in
Paris, Tunis, Lagos, Dubai and Cape Town.
Open Roles
 
PhD Research Intern
<https://www.karkidi.com/job-details/37169-phd-research-intern-job>
 
London, UK
 
Research Engineer in Reinforcement Learning
<https://www.karkidi.com/job-details/37170-research-engineer-in-reinforcement-learning-job>
 
London, UK
 
Research Engineer in Reinforcement Learning
<https://www.karkidi.com/job-details/37171-research-engineer-in-reinforcement-learning-job>
 
Boston, MA, USA
 
Research Engineer in Science
<https://www.karkidi.com/job-details/37172-research-engineer-in-science-job>
 
Boston, MA, USA
 
Research Intern (ML for Protein Structure Prediction)
<https://www.karkidi.com/job-details/37173-research-intern-ml-for-protein-structure-prediction-job>
 
London, UK
 
Research Scientist in Science
<https://www.karkidi.com/job-details/37174-research-scientist-in-science-job>
 
Boston, MA, USA
 
Senior Software Engineer
<https://www.karkidi.com/job-details/37083-senior-software-engineer-job>
 
Tunis, Tunisia
 
Software Engineer – Simulation
<https://www.karkidi.com/job-details/37084-software-engineer-simulation-job>
 
Cape Town, Western Cape, South Africa
 
Software Quality Assurance Engineering Intern
<https://www.karkidi.com/job-details/37087-software-quality-assurance-engineering-intern-job>
 
Tunis, Tunisia
 
Team Lead – Machine Learning Engineer
<https://www.karkidi.com/job-details/37088-team-lead-machine-learning-engineer-job>
 
Tunis, Tunisia
 
DevOps Engineer
<https://www.karkidi.com/job-details/37089-devops-engineer-job>
 
Tunis, Tunisia
 
Machine Learning Engineer
<https://www.karkidi.com/job-details/37090-machine-learning-engineer-job>
 
Boston, MA, USA
 
Senior Research Engineer (Physics-informed AI)
<https://www.karkidi.com/job-details/37082-senior-research-engineer-physics-informed-ai-job>
 
Berlin, Germany
 
Senior Research Engineer (Physics-informed AI)
<https://www.karkidi.com/job-details/37081-senior-research-engineer-physics-informed-ai-job>
 
Paris, France
 
Senior Research Engineer (Physics-informed AI)
<https://www.karkidi.com/job-details/37080-senior-research-engineer-physics-informed-ai-job>
 
Paris, France
 
Senior Research Engineer (Applied RL)
<https://www.karkidi.com/job-details/37077-senior-research-engineer-applied-rl-job>
 
Paris, France
 
Senior Research Engineer (Applied RL)
<https://www.karkidi.com/job-details/37076-senior-research-engineer-applied-rl-job>
 
Berlin, Germany
 
Senior Research Engineer (Applied RL)
<https://www.karkidi.com/job-details/37075-senior-research-engineer-applied-rl-job>
 
London, UK
 
Research Engineer Intern – Optimisation/RL/OR
<https://www.karkidi.com/job-details/37074-research-engineer-intern-optimisation-rl-or-job>
 
Paris, France
 
Senior Research Engineer (Physics-informed AI)
<https://www.karkidi.com/job-details/37078-senior-research-engineer-physics-informed-ai-job>
 
London, UK
 
Senior Research Engineer (Physics-informed AI)
<https://www.karkidi.com/job-details/37079-senior-research-engineer-physics-informed-ai-job>
 
Paris, France
 
Research Engineer (Applied RL)
<https://www.karkidi.com/job-details/37073-research-engineer-applied-rl-job>
 
Cape Town, Western Cape, South Africa
 
Research Engineer (Applied RL)
<https://www.karkidi.com/job-details/37069-research-engineer-applied-rl-job>
 
London, UK
 
Research Engineer
<https://www.karkidi.com/job-details/37068-research-engineer-job>
 
London, UK
 
Research Engineer (Applied RL)
<https://www.karkidi.com/job-details/37070-research-engineer-applied-rl-job>
 
Paris, France
 
Research Engineer (Applied RL)
<https://www.karkidi.com/job-details/37071-research-engineer-applied-rl-job>
 
Berlin, Germany
 
Research Engineer
<https://www.karkidi.com/job-details/37066-research-engineer-job>
 
Tunis, Tunisia
 
Machine Learning Engineer
<https://www.karkidi.com/job-details/37058-machine-learning-engineer-job>
 
Paris, France
 
AI Software Engineer
<https://www.karkidi.com/job-details/37059-ai-software-engineer-job>
 
Tunis, Tunisia
 
Data Analytics Internship
<https://www.karkidi.com/job-details/37060-data-analytics-internship-job>
 
Tunis, Tunisia
 
Machine Learning Engineer
<https://www.karkidi.com/job-details/37061-machine-learning-engineer-job>
 
Cape Town, Western Cape, South Africa
 
Machine Learning Engineer
<https://www.karkidi.com/job-details/37062-machine-learning-engineer-job>
 
Lagos, Lagos, Nigeria
 
Machine Learning Engineer
<https://www.karkidi.com/job-details/37063-machine-learning-engineer-job>
 
London, UK
 
Machine Learning Engineer
<https://www.karkidi.com/job-details/37064-machine-learning-engineer-job>
 
San Francisco, CA, USA
 
Pre-sales/Solutions Engineer
<https://www.karkidi.com/job-details/37065-pre-sales-solutions-engineer-job>
 
San Francisco, CA, USA
 
Machine Learning Engineer
<https://www.karkidi.com/job-details/37057-machine-learning-engineer-job>
 
London, UK
 
Research Engineer Intern (Deep Learning for personalized immunotherapy)
<https://www.karkidi.com/job-details/37056-research-engineer-intern-deep-learning-for-personalized-immunotherapy-job>
 
Paris, France
 
Senior Research Engineer – Bio AI
<https://www.karkidi.com/job-details/37055-senior-research-engineer-bio-ai-job>
 
Paris, France
 
Bio-Engineer
<https://www.karkidi.com/job-details/37052-bio-engineer-job>
 
Tunis, Tunisia
 
DeepChain Product Intern
<https://www.karkidi.com/job-details/37053-deepchain-product-intern-job>
 
San Francisco, CA, USA
 
DeepChain Product Intern
<https://www.karkidi.com/job-details/37054-deepchain-product-intern-job>
 
San Francisco, CA, USA
 
Computational Biologist
<https://www.karkidi.com/job-details/36935-computational-biologist-job>
 
Paris, France
 
Computational Biologist
<https://www.karkidi.com/job-details/36934-computational-biologist-job>
 
London, UK
 
Computational Geneticist
<https://www.karkidi.com/job-details/36937-computational-geneticist-job>
 
London, UK
 
Research Engineer – Bio AI
<https://www.karkidi.com/job-details/36938-research-engineer-bio-ai-job>
 
London, UK
 
Research Engineer – Bio AI
<https://www.karkidi.com/job-details/36939-research-engineer-bio-ai-job>
 
Paris, France
 
Computational Geneticist
<https://www.karkidi.com/job-details/36936-computational-geneticist-job>
 
Paris, France
 
Research Engineer – Bio AI
<https://www.karkidi.com/job-details/36940-research-engineer-bio-ai-job>
 
Cape Town, South Africa
 
Computational Biologist
<https://www.karkidi.com/job-details/36933-computational-biologist-job>
 
Tunis, Tunisia

Rutgers University

Dr. Patrick Shafto’s lab in the Department of Math and Computer Science at
Rutgers University in Newark will be accepting applications for PhD
positions starting Fall 2023. Positions are fully funded and include a
stipend.
 
The PhD program is a unique combination of training in pure mathematics
with research in machine learning. Graduates of the lab have gone on to
positions in industry and academia.
 
Dr. Shafto’s Cognitive and Data Sciences lab studies machine learning and
human learning with tools from probabilistic machine learning, pure
mathematics, and behavioral experiments. More information about the
research can be found at http://shaftolab.com/. Recent papers and preprints
represent current research directions.
 
Interested applicants should reach out to Dr. Shafto describing their
research interests and experience. Application information should be
submitted to the Mathematical Sciences PhD program through the Rutgers
website.

University of Bremen

The Computational Neurophysics lab at the University of Bremen headed by
Dr. Udo Ernst offers – under the condition of job release – at the earliest
possible date a position until 30.09.2024:
 
 
*Research Assistant in Computational Neuroscience (f/m/d)*
 
German federal pay scale E13 TV-L (65 %)
 
for the research project
 
 
*I-See2 – Improving Intracortical Visual Prostheses Using Complex Coding
and Spontaneous Activation States*
 
 
The lives of many individuals are strongly impaired by missing the sense of
vision. One putative option to help them are cortical prostheses. Such
devices record images from our environment, encode this information into
the ‘language’ of the brain, and stimulate neuron populations in the visual
system for creating a corresponding percept.
 
 
I-See2 (www.isee.uni-bremen.de) investigates new principles for building
cortical prostheses in an international group with researchers from Canada,
Switzerland and Germany. Your position will be at the heart of the project
in Bremen, where computational methods are developed and data from our
partner labs comes together. You will perform modelling of visual
information processing, analysis of data from electrophysiological
multielectrode recordings and optical voltage imaging, and be involved in
model-driven visual stimulus generation for animal and human experiments.
The position comes with direct supervision by the principal investigators
and project coordinators Dr. David Rotermund and Dr. Udo Ernst.
 
 
*Requirements:*
 
Ideal candidates have a master’s degree in Computational Neurosciences,
Physics, Computer Sciences or in related fields. They must have a strong
background in neural networks, dynamical systems, mathematics and/or data
analysis, and be experienced in programming (preferably in Python/Matlab).
Above all, they must have a strong motivation, a sense for responsibility,
a distinct desire to learn, and the ability to proactively collaborate in
an international research environment. Fluency in English is required (both
written and spoken).
 
 
The Computational Neurophysics Lab offers a good working atmosphere, direct
involvement in international research and attractive facilities.
 
The university is family-friendly, diverse and sees itself as an
international university. We therefore welcome all applicants regardless of
gender, nationality, ethnic and social origin, religion/belief, disability,
age, sexual orientation and identity.
 
As the University of Bremen intends to increase the proportion of female
employees in science, women are particularly encouraged to apply. In case
of equal personal aptitudes and qualification priority will be given to
disabled persons.
 
Please explicitly address each of the specified requirements in the
application. Detailed instructions are described below. Please send your
application documents (motivation letter, CV, copy of your degree
certificates including high school, list of skills, awards, publications,
contact details of two academic reference) until December 9th, 2022 by
indicating the job id A325/22 to:
 
University of Bremen FB1
Computational Neurophysics lab
Secretary of Dr. Udo Ernst
Mrs Agnes Janßen
Hochschulring 18, Cognium
D-28359 Bremen
Tel.: +49 421 218 62000
 
or in electronic form in a summarized PDF file via e-mail:
ajanssen@neuro.uni-bremen.de.
 
 
For questions of the research project please contact:
 
Dr. Udo Ernst, E-Mail: udo@neuro.uni-bremen.de
 
 
See also for general information on this topic:
 
http://www.isee.uni-bremen.de
 
 
*Detailed instructions for applicants*
 
Your application must comprise:
 
 
*Motivation letter*
 
Your 1-2 page essay should reply the following questions:
 
• What is your background? In which fields have you worked before and how
do you think this can be useful for the present job?
 
• What attracts you to the field of computational neuroscience?
 
• Which problem(s) in computational neuroscience are you most interested in?
 
• What is your motivation to join our project?
 
• What are your plans for your future career?
 
 
*Curriculum Vitae*
 
Send a classical tabular CV with your contact details, and all stages of
education and employment.
 
 
*List of skills, awards, publications*
 
List your skills, especially proficiency in languages (including the level
of proficiency), that you think might be useful for the job. Also list
awards you might have got and peer-reviewed papers, in case there are some.
 
 
*Contact details of two academic references*
 
One of the references should be your MSc advisor. Please contact the
references prior to listing their names so that they are not surprised if
they get contacted.
 
Your application can be in English or German, whatever language you are
more familiar with.

Konrad Zuse School of Excellence in Reliable AI

The *Konrad Zuse School of Excellence in Reliable AI (relAI)*
<https://zuseschoolrelai.de/> aims to train future generations of
artificial intelligence (AI) experts, who for the first time combine
technical brilliance with awareness of the importance of AI’s reliability.

 
*Applications for the relAI PhD program are now open*
 
The current technological revolution is largely driven by spectacular
progress in AI. Yet, although the huge potential is widely recognized, the
lack of a reliable AI technology whose fundamental bases are safety,
security, privacy and responsibility, is still considered a serious issue
of concern, limiting its adoption both by industry and society at large.
 
The relAI program focuses on the mathematical and algorithmic foundations
of reliable AI along with domain knowledge in three core application areas
for which reliable AI methods are most urgently needed: medicine &
healthcare, robotics & interacting systems, and algorithmic decision-making,
 
The relAI school is embedded in the unique transdisciplinary Munich AI
ecosystem, combining the expertise of the two Universities of Excellence*
Technical University of Munich (TUM) and Ludwig Maximilians University of
Munich (LMU)* and closely integrates various AI Centers of leading
universities worldwide and industry partners.
 
*What the relAI PhD program offers*
 
The novel, innovative PhD relAI program offers a cross-sectional training
for successful education in AI including scientific knowledge, professional
development courses and industrial exposure, providing a coherent, yet
flexible and personalised training.
 
Funded applicants will be hired for three years, including social benefits
(TV-L E13 of the German public sector). They are further supported by
travel grants, e.g. for conference attendance or research stays. Doctoral
students enrol at TUM or LMU depending on the hosting relAI fellow.
<https://zuseschoolrelai.de/fellows-overview/>
 
*Eligibility*
 
Excellent master’s degree (or equivalent)* in computer science,
mathematics, engineering, natural sciences or other data science/machine
learning/AI related disciplines.
 
Applicants should have a genuine interest to work on a topic of reliable AI
covering aspects such as safety, security, privacy and responsibility in
one relAI’s research areas Mathematical & Algorithmic foundations,
Algorithmic Decision-Making, Medicine & Healthcare or Robotics &
Interacting Systems.
 
*How to apply*
 
Applications are sent online via this website
<https://zuseschoolrelai.de/application/>. We refer interested candidates
to the relAI website <https://zuseschoolrelai.de/application/> for more
information about the call requirements.
 
Deadline for applications is *January 9th, 2023*.
 
*If you are still studying for your master’s degree you may send a bona
fide statement/transcript from the university, stating the examination
marks already obtained. In addition, you will have to finish your master’s
studies before starting the PhD.

University of Texas

*Position Information:* *immediate fill of fully funded Ph.D. positions for
Fall/Spring 2023* at the Center on Stochastic Modeling, Optimization, &
Statistics (COSMOS) at the University of Texas at Arlington. Graduate
students with *strong quantitative background and programming skills* are
encouraged to apply. The research directions include *Advanced* *Analytics,
Deep Learning*, *Machine Learning, *and *AI-driven Intelligent UAV-UGV
Systems. *
 
If you are interested, please send your CV to *Dr. Shouyi Wang at *
*shouyiw@uta.edu* <shouyiw@uta.edu>. We will evaluate your CV and give
feedback quickly. *Accepted Ph.D. students will work with Dr. Wang and will
be provided** with full financial support for the entire Ph.D. study*. *Visiting
Students/Scholars Positions *are also available in Deep Learning and
Intelligent Systems.
 
*Lab** Information: *The COSMOS Center is conducting world-leading research
in Advanced Data Analytics, Machine Learning Research, Complex System
Optimization & Modeling, Healthcare, and Biomedical Informatics, and
AI-driven Technologies. The lab has very strong connections to the AI
industry. The renowned research collaborators include *American Airlines,
Apple, Foxconn, IBM, Facebook/Oculus, Samsung/Harman AI Group, and NVIDIA.*
 
*The COSMOS Center Ph.D. graduates are highly competitive in the US job
market.* Recent Ph.D. graduates of COSMOS Center obtained jobs at *American
Airlines,** United Airlines, UPS, CSX, AT&T, Alibaba/Seattle, Bank of
America, BNSF, General Motors, etc.* *Our Ph.D. graduates also have immense
opportunities to pursue academic careers. *Recent Ph.D. students obtained
faculty positions at top schools, including the *University of Illinois
Chicago, Washington State University, Stevens Institute of Technology,
University of Southern California, The State University of New York at
Buffalo, Harbin Institute of Technology, etc*.
*The Current Research Projects & Topics include:*
* Deep Learning for drug discovery (e.g., protein, DNA/RNA, molecule deep
learning in life science, sponsored by NSF & NIH)
* Deep Learning for medical imaging analytics (work with the University of
Washington)
* AI-Driven UAV-UGV Collaborative Smart Systems for Agriculture
Applications (work with USDA)
* Probabilistic Deep Learning and Stochastic Optimization for Complex
Systems Decision Analytics with Applications to Energy Systems and Smart
Grids Operations Management (NSF)
* Interpretable Deep Learning/Machine Learning Research for Biomedical Data
Mining & Knowledge Discovery
* Deep Learning for Satellite Imaging Analytics and Geographic Information
Systems (USDA)
 
*School Information:* With more than *50,000* enrolled students, UTA is one
of the largest public universities in the nation. According to the 2022
U.S. News and World Report, *UTA Engineering School is ranked #79 in the US
<https://www.usnews.com/best-graduate-schools/top-engineering-schools/university-of-texas-arlington-02177#:~:text=The%20University%20of%20Texas%20at%20Arlington%20is%20ranked%20No.,widely%20accepted%20indicators%20of%20excellence.&text=See%20how%20this%20school%20scored,indicators%20used%20in%20the%20rankings.>*.
The Industrial, Manufacturing, & Systems Engineering (IMSE) Department is
ranked *#50* for Graduate Programs
<https://www.uta.edu/uta/about/rankings.php>. With great resources and
Texas State support, the IMSE department is one of the fastest-growing
programs in the US with more than 500 graduate students. UTA is one of the
146 Carnegie R-1 Doctoral Universities in the US with the highest research
activities.
<https://en.wikipedia.org/wiki/List_of_research_universities_in_the_United_States#Universities_classified_as_%22R1:_Doctoral_Universities_%E2%80%93_Very_high_research_activity%22>
*DFW/Arlington Area:* Located in the US’s 4th largest metropolitan area
(Dallas/Fort Worth Area), the COSMOS Center at UTA is conducting
world-leading research projects and has strong industry support and
collaborations.

Uppsala University

Open PhD position: a fully funded PhD position towards Bayesian
computational methods in Epidemics, specifically using non-traditional
sources of data. The tentative project title is simply “Computational
Epidemics”; more information about this project can be found here:
https://user.it.uu.se/~stefane/formalia/TDB2022_SLL-eSSENCE-PhD.pdf
 
Apply via the online system:
https://www.uu.se/en/about-uu/join-us/details/?positionId=555466
 
Earliest starting date: January 2023 (and as agreed). Deadline to apply
December 16th!
 
This position is placed at the newly created eSSENCE-SciLifeLab graduate
school in data-intensive science and thus comes equipped with travel
funding, newly created PhD courses, and an overall dynamic environment. A
bit more information can be found here:
https://essenceofescience.se/graduate-school/