(Apologies for cross posting)

Dear colleagues, We offer a 12 months position for a junior engineer in computer vision and deep learning, at Mines ParisTech and in partnership with Safran Aircraft Engines.

Although it is not secured yet, we hope to offer a PhD position as follow up of this contract.

More details here:

(french) https://cloud.mines-paristech.fr/index.php/s/Y3oXdaiBmLj4PnU

(english) https://cloud.mines-paristech.fr/index.php/s/rjp0b5f2yxee1Xz

Best, Santiago Velasco-Forero Samy Blusseau

PhD position in Multimodal Grounding for Robotic Assistants (ANITI, Toulouse, France)

The Artificial and Natural Intelligence Toulouse Institute (ANITI: https://aniti.univ-toulouse.fr/en/) in Toulouse (France) is looking to recruit a PhD student in Machine Learning to work on multimodal grounding (e.g., joint vision-language models).

The selected candidate will develop deep learning models capable of achieving state-of-the-art performance on cognitively challenging problems such as: Visual Question Answering, Incremental Learning, Meta-Learning, Multi-Task Learning, Task-Switching, Robust Representation Learning, etc.

The candidate will join an active group of like-minded students (the ANITI Graduate School) and a vibrant research community (made up of nearly 30 ANITI Research Chairs). Work will be carried out in the Chair of Rufin VanRullen (https://rufinv.github.io) at CerCo (https://cerco.cnrs.fr), but in close collaboration with local and international research groups (IRIT, LAAS, Linagora, University of Potsdam, Airbus AI research).

Rufin VanRullen’s ANITI Chair is entitled “Deep Learning with Semantic, Cognitive and Biological Constraints”, and aims at fostering next-generation AI architectures by drawing inspiration from Cognitive Sciences and Neuroscience.

The PhD project is part of a large-scale France-Germany collaborative grant entitled “Natural Language Programming for Conversational Cobots”.

The multi-modal grounding research will need to assist the overall grant objectives (ultimately, helping robotic assistants interact with humans in natural language), but there will also be freedom to pursue independent research questions related to multimodal grounding in AI and/or in the brain.

The ideal candidate will have a Masters in Computer Science, Machine Learning or related fields, and substantial experience with at least one deep learning framework (PyTorch, Tensorflow, Keras…).

Research experience in Computer Vision, NLP and/or Reinforcement Learning is highly desirable. The salary scale is according to ANITI standards.

The position is open to start immediately, but applications will be considered until the position is filled.

To apply, send a CV and a short (less than 1-page) statement about research interests to [email protected]. Informal inquiries can also be made to the same address.

Rufin VanRullen, PhD. < ANITI - AI Research Chair > Artificial & Natural Intelligence Toulouse Institute CNRS-Centre de Recherche Cerveau & Cognition (CerCo) Faculte de Medecine Purpan - 31052 Toulouse (France)

email: [email protected]

Web: https://rufinv.github.io/

Tel: +33 669 547 468

The Department of Communications and Computer Engineering at the University of Malta is offering a postdoc position until October 2023 to work on the VoLARe Project.

The research conducted by the selected candidate will mainly focus on the development of a novel Light-Field depth estimation method from a sparse set of cameras.

The estimated depth map will then be used to synthesize intermediate views.

This project is a collaboration with Stargate Studios Malta is a video production company that will use the developed video light field capturing system in a production.

Candidates with a background in Computer Vision, Image Processing, Machine Learning and AI are encouraged to apply.

More information about the call can be found here. https://www.um.edu.mt/__data/assets/pdf_file/0008/478952/RSOIIorIII-VOLARE-18.10.2021.pdf

If you have any queries, please do not hesitate to contact us on [email protected].

We look forward to receiving your submissions.

Postdoctoral position in Computer Vision / Machine Learning

Job description The division of Computational Science and Technology at KTH Royal Institute of Technology in Stockholm, Sweden is seeking a Postdoc in Computer Vision / Machine Learning to handle scale-dependent image information in deep networks.

In our research, we develop deep networks for processing image data that handle scaling transformations and other image transformations in a theoretically well-founded manner.

Our research in this area comprises both theoretical modelling of the influence of image transformations on different architectures for deep networks and the experimental evaluation of such networks on benchmark datasets to explore their properties.

The work also comprises the creation of new benchmark datasets, to enable characterization of properties of deep networks that are not covered by existing datasets. For examples of our previous work in this area, see https://www.kth.se/profile/tony/page/deep-networks

Within the scope of this postdoc position, you are expected to work on and contribute to the research frontier regarding scale-covariant or scale-equivariant deep networks and/or deep networks parameterized in terms of Gaussian derivatives, on specific research topics that we choose together.

The selected candidate will work closely together with the project leader Tony Lindeberg.

For further information and information about to how to apply, see https://kth.varbi.com/en/what:job/jobID:432053/

Application deadline: November 1, 2021

Dear colleagues and students, The CRVL (Computer and Robot Vision Lab) of the Kyungpook National University, Daegu, Korea has open positions. We're looking both for enthusiastic PhD students and post-doctoral researchers. More specifically, we have the following open positions

* Computer Vision for 3D Reconstruction

- 3D reconstruction from Two -view Stereo Vision

- 3D reconstruction from Multi-view Stereo Vision

- Deep neural network for Mono-view 3D (Depth) Reconstruction

* 6D Pose Estimation for Robot Bin Picking - Working on deep neural networks to estiamte the 6D pose of indoor objects from an RGBD image

- Working on 3D graphic model to RGBD matching

* Visual SLAM for robot - Working on indoor and outdoor visual SLAM for autonomous vehicles or robots

Salary * Post-doctoral position: $2200~$2500/month plus insurance (this is a very good salary for the living costs in Daegu, Korea).

* Ph.D student: $1500~$2200/month

The post-doctoral position is for a maximum of 24 months, however it can be extended.

I will be the supervisor, please contact with me at [email protected] for more information.

Thanks in advance, Soon-Yong Park Professor/Ph.D.

School of Electronics Engineering Department of Robot and Smart System Engineering Kyungpook National University

IT-1 Building #413 Dahak-ro 80, Puk-gu Daegu, 41566 South Korea Phone: +82-53-950-7575 Fax: +82-53-950-5505

Email: [email protected]

Lab Homepage: http://vision.knu.ac.kr

University Homepage: http://knu.ac.kr

Dear all, We are looking for a PhD student to work on unsupervised keyphrase generation for scholarly documents.

If your profile its the description below and you are interested, please send your CV and application documents at [email protected] and / or [email protected]

Best regards, Florian Boudin - Ass. Teacher. / LS2N - University of Nantes, France Béatrice Daille - Full Prof. / LS2N - University of Nantes, France

Fully-funded 3-years PhD position on unsupervised keyphrase generation for scholarly documents

Keywords: Information Retrieval, Natural Language Processing

Funded by the French National Research Agency (ANR) through the DELICES project (ANR-19-CE38-0005-01). Salary is approx. 1500 € per month. Funds are secured for travels to international conferences.

Location: Nantes, France

Starting date is flexible, starting from 11/01/2021.

Profile: a university degree (MSc) in Computer Science is required, with solid experience in deep learning. Interests in Natural Language Processing, information retrieval or artificial intelligence are a definite more.

Strong programming skills (Python) and excellent English skills are expected. Fluency in French is not required for admissions.

PhD's research topic: this PhD falls within the context of scientific digital libraries (eg arXiv, Pubmed) and will focus on developing new keyphrase-based indexing models to simplify and ease the access to scientific articles. More specifically, the task will be to develop unsupervised methods for keyphrase generation with the primary objective of producing absent keywords, that is, that do not occur in the the document.

Please send applications including motivation, curriculum vitae and certificates to Florian Boudin and / or Béatrice Daille by email via [email protected] and / or [email protected] . If your application is accepted, you will be offered an audition.

From: "Cassia TROJAHN" [email protected] Date: Mon, 25 Oct 2021 11:37:27 +0200

Bonjour à tous, (Désolée pour les réceptions multiples)

Nous recrutons un post-doc à l'IRIT sur le liage de données dans le cadre de l’ANR DACE-DL : DAta-CEntric AI-driven Data Linking Le recrutement est prévu tout début 2022 pour 24 mois.

Merci de faire circuler ces deux offres dans vos réseaux.

Cordialement, Cassia Trojahn et Olivier Teste

** Post-doctoral position at IRIT: Data Linking ** Context: ANR project DACE-DL (DAta-CEntric AI-driven Data Linking)

Data linking is the scientific challenge of automatically establishing typed links between the entities of two or more structured datasets.

A variety of complex data linking systems exists, evaluated on public benchmarks. While they have allowed for the generation of vast amounts of linked data in the context of various dedicated projects, data generic systems often have limited applicability in many real-world scenarios, where data are highly heterogeneous and domain-specific.

DACE-DL targets a paradigm shift in the data linking field with a data-centric bottom-up methodology relying on machine learning and representation learning models. We hypothesize there exists a finite number of identifiable and generalisable linking problem types (LPTs), that we need to categorize and analyse to provide better linking results.

Topic: Data collect, consolidation, and data linking systems modularization

This research is articulated in two main tasks. The first task consists in (1) carrying out an in-depth analysis of the quality of the existing data linking datasets, identifying erroneous statements and providing a high-quality set of datasets by correcting those statements; and

(ii) generating additional links using existing high-precision linking systems on the chosen datasets. Data quality metrics such as accuracy, consistency and conciseness will be considered.

The aim of the second task is manifold : (1) to provide an inventory of publicly available and functional linking tools that are able to deal with a large spectrum of data linking problem;

(2) to propose a theoretical approach for the modularization of these tools into atomic modules easy to combine in order to build more complex solutions in a linking ecosystem;

(3) to make the produced modules available to the data linking community. To do the modularization at scale, we plan to call upon unsupervised ML algorithms, enhanced by a human-in-the-loop approach. The objective is to provide a set of correspondences between the modules and the LPTs.

Starting period: January 2022 – duration of 24 months

* Work environment and Salary *

Localization : Institut de Recherche en informatique de Toulouse (IRIT) – Universite Toulouse - Jean Jaures / Maison de la Recherche, 5, allees Antonio Machado 31058 Toulouse. Salary between 2200€ and 2700€ gross monthly depending on qualifications and situation.

* How to apply * Applicants are required to have a PhD in Computer Science, a strong background in semantic web technologies, ontology matching and data linking. Fluency in written / spoken English is required too. A good publication record and strong programming skills will be a plus.

Applications will be accepted until the position is closed. Applicants should send a full CV including a complete list of publications, a cover letter indicating their research interests, achievements to date and vision for the future, as well as either support letters or the name of 2 persons that have worked with them.

Contact: Cassia Trojahn ([email protected]) and Olivier Teste ([email protected])

The offer in detail: http://www.univ-lemans.fr/_resource/Universite/S_engager_a_nos_cotes/Recrutement/ATER-CTER/27CTER0532.pdf

== INFORMATION == Recruitment open: until October 16, 2021 before 4 p.m.

Quotity: 100%

Contract duration: from 12/01/2021 to 08/31/2022

CNU section: 27

== Research == Laboratory URL: http://www-lium.univ-lemans.fr

Contact person (s) (Name, function, phone, email): Sébastien George, director of the laboratory, 02 43 59 49 16, [email protected]

** Two team: ** 1.one of fourteen ECs specializing in environments computer science for human learning (EIAH Engineering), directed by Sébastien Iksal;

2.one from EC specialized in speech recognition, machine translation (Language and Speech Technology - LST) and text mining, directed by Sylvain Meignier

== Teaching == At the IUT of Le Mans: Office automation (spreadsheet), Database management system, Information system, Business intelligence, project management and internship monitoring.

Contacts for the teaching profile (Name, function, phone, email):

Xavier PALLARD, head of department, 0615882258, [email protected]

Nicolas DUGUÉ, lecturer in computer science, [email protected] -

Security hardening based on multi-agent system verification in the context of the connected car infrastructure

Keywords: Security, Formal Verification, Model Checking of Multi-Agent Systems, Security Risk Management, Attack Modelling

Description Recently, classic verification approaches such as model checking have been extended to handle multi-agent systems. These are systems that encapsulate the behavior of two or more rational agents interacting among them in a cooperative or adversarial way, aiming at a designed goal. In system security checking, a malicious attack can be seen as an attempt of an intruder to gain unauthorized access to a resource or as an attempt to compromise the system integrity. The envisioned approach is: given an attack model of the system (such an attack graph), to model the interactions between the attacker & defender as a game on this attack model and use multi-agent system verification techniques to determine optimal defense strategies.

Goals The global objective of this postdoc is the use of methods and tools for security hardening in the context of the connected car infrastructure based on a formal verification approach.

Some of the challenges of this postdoc will be to answer to the following questions:

How can we select security counter-measures ensuring the best trade-off between security level achieved and other constraints?

How can we capture the dynamic between the attacker and the defender?

How can we integrate these decision support tools in the classical risk management process such as defined by the ISO/IEC 27005 without redefining it completely?

Profile and skills required

- PhD in computer science, mathematics, or related fields.

- Strong computer science and/or mathematical background (with particular attention on formal methods, logic, and security).

- Good programming skills.

- Good level in written and spoken English.

How to apply If you are interested you can apply by sending your CV and motivation letter to: [email protected] and [email protected]

Deadline for application submission: October 29, 2021.

Hello, We are pleased to provide you with an offer 12-month post-doctorate , to complete the Interreg ParkinsonCom project team ( https://parkinsoncom.eu ) which aims develop a communication aid tool for people with Parkinson's disease.

Detailed offer is available at: http://www.uphf.fr/LAMIH/sites/fr.LAMIH/files/pdf/info/annonce_post-docparkinsoncomoctobre.pdf

Best regards, Káthia Oliveira, Sophie Lepreux and Christophe Kolski

Postdoctoral researcher in Computational Diachronic Semantics

Labex EFL (Empirical Foundations of Linguistics, Paris, https://en.labex-efl.fr/)

Strand 5: Computational Semantic Analysis

Research area : interpretable computational models for automatic detection and monitoring of semantic evolutions: combination of Contextual Embeddings and Pattern Mining approaches

Contract duration: 18 months

Location: Paris

Research Laboratory: Sorbonne Paris Nord University, LIPN UMR7030 CNRS

Application deadline: November 15, 2021

Audition period: November 15-30, 2021

Job Starting date: from January 1, 2022

Context, Issues and research axes Languages ​​are constantly evolving, driven by the need to adapt to socio-cultural and technological developments and to make communication more efficient and expressive. In particular, new words are forged or borrowed from other languages, some words become obsolete, others acquire new meanings or lose existing meanings.

In NLP, the study of language dynamics, especially from the lexical point of view, has gained audience in recent years, complementing synchronic approaches. The field of research is structuring itself, with recent state of the art (Monteirol et al., 2021; Tahmasebi et al., 2021) and several scientific events (International Workshop on Computational Approaches to Historical Language Change 2019 and 2021, ACL 2019 and 2020). Two initial evaluation tasks have been proposed (Unsupervised Lexical Semantic Change Detection Task, SemEval2020) and reference sets have been set up for four languages ​​(English, Latin, Swedish and German).

Lexical change detection systems have followed advances in NLP methods: after the first systems essentially based on frequency changes (for example Gulordova & Baroni, 2011), systems used word embeddings (Kim et al., 2014, Schletchweg et al., 2019) and more recently contextual embeddings (Hu et al., 2019; Martinc et al., 2019; Giulianelli et al., 2020). These latter systems generally proceed by grouping the contextual vector representations of the different uses into clusters of meaning, then detect changes according to different metrics (Monteirol et al. 2021).

Current systems still face many limitations. Mainly, the opacity of neural models does not make it possible to characterize these evolutions, in particular it is difficult, if not impossible, to link the semantic changes to linguistic morphological, syntactic or lexico-syntactic features, or to categorize the types of changes (extension, restriction, metaphor, metonymy, etc.). To this end, one avenue would be to combine neural approaches with Pattern Mining (Béchet et al. 2015) or collocation extraction approaches from corpus linguistics (for example Gries, 2012) which make it possible to extract the most salient lexico-syntactic patterns of a given meaning from a corpus of occurrences and thus identify the evolution. It would also be interesting to use the contextual information of the occurrences (date, type of source, domain, diatopic and diastratic features, etc.) to characterize and follow the evolution of usages.

The job main objective is therefore to set up a system combining these approaches to allow an automatic characterization of semantic evolutions. The first step will consist in experimenting with state-of-the-art models for detecting changes. The second step will then try to combine contextual embeddings and pattern mining approaches / collocation extraction to highlight the linguistic characteristics of each of the meaning clusters and their evolution. The studied corpora will be mainly in English and French. The postdoctoral fellow will work in collaboration with computer scientists and linguists from the Labex who are currently building a reference corpus of semantic evolutions for French (following the Durel methodology: Schlechtweg et al., 2018).

Other issues may also be addressed by the recruited person, and in particular: current systems do not take into account the graduality of evolutions, generally being limited to comparing two synchronic language states; to get the vector representation of a lexis in a context, it is possible to use one of the hidden layers or a combination of them. There is currently no consensus on the most adequate layer to take into account to obtain the most adequate semantic representation.

The recruited person will join the strand 5 (“Computational Semantics”) of the Labex, specifically the research team working on the “Semantic Variation and Change” operation which aims to:

develop new models and methods for the automatic detection of lexical semantic changes, the typology of changes from intra- and extra-linguistic points of view;

develop a reference dataset of semantic evolutions in contemporary French, based on available diachronic corpora.

Candidate profile - PhD in computer science specialised in Computational Linguistics and Machine Learning

- deep learning methods and language models attested training and experience

- working language: French and / or English

Application

Please send : • a cover letter

• a description of the research project related to the research questions

• a CV with a list of publications and 3 representative publications (pdf or link),

• letters of recommendation or names of two referees.

to [email protected] and [email protected] before November 15, 2021. The auditions of the pre-selected candidates will take place at the end of November 2021.

Hello, The LGP laboratory of the National Engineering School of Tarbes offers a 6-month internship at the end of the Engineering course or the end of a Master, to start in February 2022. This internship is funded by the H2020 CSA OntoCommons project ( https://ontocommons.eu/ ) . Details are available below:

Duration of the internship : 6 months

Start date : February 01, 202 2

Host unit : LGP Laboratory of the National Engineering School of Tarbes , Tarbes, 6500, France

Framing : Mohamed H e di Karray and Emna Amdouni

Deadline : January 15, 2022

Skills and technologies : A Web rchitecture, Devops, data management, s ervices Web RES T / JSON, Ruby / Ruby on Rails, Java EE, Linux and Git.

Description : The internship is offered as part of the European H2020 CSA OntoCommons project ( https://ontocommons.eu/ ) started in 2020 . OntoCommons aims to standardize , harmonize and interoperate industry data via a common repository of semantic resources and tools called OCES ( Ontology Commons EcoSystem ).

The internship therefore aims to set up a dedicated portal of semantic resources ( thesaurus, terminologies, vocabularies and ontologies) identified in the phase of design of OCES repository. The objective of u portal is to facilitate interoperability data from the field of industry via web services mainly related to hosting, alignment , annotation and analysis . W e hope that the planned portal will be set up by the trainee based on technology developed by the National Center for Biomedical Ontology (NCBO) (http://bioportal.bioontology.org ) . Note that c ette technology is publicly available via the following ispositif of virtual ( http://www.bioontology.org/wiki/index.php/Category:NCBO_Virtual_Appliance ), Pla information ( https://github.com / ncbo ) .

The activities of the internship concern: The study of the Web application by BioPortal already in place

T portal deployment and testing in collaboration with external partners

Putting the portal into production

The accommodation of a few semantic resources within the portal

Profile research : BAC + 4 or BAC + 5 level in computer science

Web development training, s system administration and database

Development experience and knowledge of the following technologies: Web Services REST / JSON, Ruby / Ruby on rails, JEE and Linux

Ability to work on Git version software

Basic knowledge of Semantic Web technologies is preferred

Motivated, autonomous and technical decision- maker

Possibly interested in promoting research results

Gratuity : around 550 euros net per month.

To apply, please send your CV and transcripts from previous academic years to [email protected] and [email protected] .

Do not hesitate to disseminate this subject to your students if you think it is relevant.

Smart cities and fog computing In the context of smart cities, infrastructures and services are geographically distributed such as fog and edge computing with fixed and mobile entities.

The aim to map the graph of the infrastructure with the one of the services to be deployed.

The goal of this postdoc is to optimize the services deployment under different constraints and objectives (such as Quality of Service, Energy Consumption, ...).

This post-doc will: ▪ Formalize the problem;

▪ Explore different possible heuristics;

▪ Develop a simulator to evaluate classical algorithms of the literature.

The project is in the context of the Vilagil (funded by Toulouse Metropole) project at IRIT (http://www.irit.fr) in Toulouse. As an application, the postdoc will develop algorithms to place multi-modality mobility services on the Fog infrastructure of Toulouse Metropole.

For more information contact Georges Da Costa ([email protected]) and Patricia Stolf ([email protected]) of the SEPIA team. The main research topics of the SEPIA time are optimisation of datacenter (multi-objective scheduling).

Expected abilities of the applicant, one or more of the following ▪ Distributed systems

▪ Optimization techniques (A.I, Multi-Agent System)

▪ Graph theory

▪ Fog/Edge computing

Application: You can submit your application (CV/Cover Letter) to Georges Da Costa ([email protected]) and Patricia Stolf ([email protected])

We will evaluate application as we go along.

The post-doc duration is one year and can be renewed once for another year.

Salary starts at 2650€ brut and increases depending on previous research experience.