[UAI] Machine Learning Research Engineer position at NYU School of Medicine

[Krzysztof Jerzy Geras]

 The Center for Biomedical Imaging and the Center for Advanced Imaging
Innovation & Research (CAI2R) at NYU Langone Health are looking for a
highly motivated Research Engineer to join our interdisciplinary group and
help us build infrastructure for research on deep learning for medical
image analysis. The engineer will support ongoing research and development
of machine learning methods for medical imaging applications, such as ML
methods for accelerated MRI [1, 2, 3], breast cancer detection [4, 5, 6]
and musculoskeletal [7] and brain image [8,9,10] analysis.

*Requirements include:*

   - Passion for engineering and research.
   - Dedication and attention to detail.
   - Ability to work in large interdisciplinary teams.
   - BS in computer science, mathematics, physics, electrical engineering
   or a related discipline. MS or PhD is a plus.
   - Expert skills in Python. Skills in PyTorch or Tensorflow are a plus.
   - Good skills in using Linux and tools such as git and Docker.
   - Practical basic knowledge of machine learning. Advanced knowledge of
   machine
   learning, especially deep learning, is a plus.
   - Experience in working with medical imaging data is a plus.

*Responsibilities will include:*

   - Extraction and curation of imaging data set across different
   applications.
   - Implementation of machine learning training and validation pipelines.
   - Implementation of baseline deep learning models.
   - Building novel deep learning models tailored to medical image analysis.

*Timeline, Salary, and Benefits*
Please apply no later than 3/31/2021.
We expect the appointed candidate to start during the summer or fall 2021.
The initial appointment will be for a year, with an intention to renew
further, depending on mutual agreement. We offer a competitive salary and
benefits package. We welcome both domestic and international applicants.

*To Apply*
Please send your application (CV and a short motivation letter) to Yvonne
Lui (yvonne@nyulangone.org ) and Krzysztof
Geras (k.j.ge...@nyu.edu). Please use the string “[machine learning
research engineer 2021]” as the subject of the email.

*About Us*
The Center for Advanced Imaging Innovation & Research (CAI2R), located in
midtown Manhattan, is operated by the research arm of the radiology
department of NYU Langone Health. The research division comprises
approximately 130 full-­time personnel dedicated to imaging research,
development, and clinical translation. We are a highly collaborative group
and work in interdisciplinary, matrixed teams that include engineers,
scientists, clinicians, technologists, and industry experts. We encourage
collaboration across research groups to promote creativity and nurture an
environment conducive to breakthrough innovations at the forefront of
biomedical research. We have access to datasets of massive sizes and
computational clusters with over 300 cutting edge GPUs.

To learn more about our research center, visit https://cai2r.net

*References*
[1] Learning a variational network for reconstruction of accelerated MRI
data . K.
Hammernik et al. MRM, 2018.
[2] Assessment of the generalization of learned image reconstruction and
the potential for transfer learning . F.
Knoll et al. MRM, 2019.
[3] fastMRI: An Open Dataset and Benchmarks for Accelerated MRI
. J. Zbontar et al. 2018.
[4] Deep Neural Networks Improve Radiologists' Performance in Breast Cancer
Screening . N. Wu et
al. IEEE TMI, 2019.
[5] Globally-Aware Multiple Instance Classifier for Breast Cancer Screening
. Y. Shen et al. MLMI, 2019.
[6] Breast density classification with deep convolutional neural networks
. N. Wu et al. ICASSP,
2018.
[7] Segmentation of the proximal femur from MR images using deep
convolutional neural networks
. C. M. Deniz et al.
Scientific Reports, 2018.
[8] On the design of convolutional neural networks for automatic detection
of Alzheimer's disease . S. Liu et al.
2019.
[9] DARTS: DenseUnet-based Automatic Rapid Tool for brain Segmentation
. A. Kaku et al. 2019.
[10] Generalized Recurrent Neural Network accommodating Dynamic Causal
Modeling for functional MRI analysis
. Y. Wang et al. Neuroimage,
2018.
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[UAI] CFP - 11th IEEE Workshop on Parallel / Distributed Combinatorics and Optimization (PDCO) in conjunction with IEEE IPDPS 2021

[Grégoire DANOY]

Please, accept our apologies in case of multiple copies of this CFP.


***
 The 11th IEEE Workshop on Parallel / Distributed
   Combinatorics and Optimization (PDCO 2021)

 https://pdco2021.sciencesconf.org/

 held in conjunction with
   the 35th IEEE International
   Parallel and Distributed Processing Symposium (IPDPS'2021)
   May 17-21, 2021

 Portland, USA
http://www.ipdps.org
***


Scope:
==
The IEEE Workshop on Parallel / Distributed Combinatorics and Optimization aims 
at providing a forum for scientific researchers and engineers on recent 
advances in the field of parallel or distributed combinatorics for difficult 
optimization problems, ranging from theoretical to applied problems. The latter 
include for instance 0-1 multidimensional knapsack problems and cutting stock 
problems, large scale linear programming problems, nonlinear optimization 
problems, global optimization and scheduling problems.

Emphasis will be placed on new techniques for solving difficult optimization 
problems, like cooperative methods for integer programming problems, 
nature-inspired techniques and hybrid methods. Aspects related to Combinatorial 
Scientific Computing (CSC) will also be treated. We also solicit submissions of 
original manuscripts on sparse matrix computations and related topics 
(including graph algorithms); and related methods and tools for their 
efficiency on different parallel systems. Applications combining traditional 
parallel and distributed combinatorics and optimization techniques as well as 
theoretical issues (convergence, complexity, etc.) are welcome.

Application domains of interest include (but are not limited to) cloud 
computing, planning, logistics, manufacturing, finance, telecommunications and 
computational biology.


Topics:
===
* Exact methods, heuristics, metaheuristics, hybrid methods;
* Parallel / distributed algorithms for combinatorial optimization;
* Parallel / distributed  metaheuristics;
* Nature inspired parallel / distributed computing;
* Integer programming, linear programming, nonlinear programming;
* Global optimization, polynomial optimization;
* Cooperative methods, hybrid methods;
* Parallel sparse matrix computations, graph algorithms, load balancing;
* Applications: cloud computing, planning, logistics, manufacturing, finance, 
telecommunications, computational biology, combinatorial algorithms in high 
performance computing.


Steering Committee:
===
Pascal Bouvry, University of Luxembourg, Luxembourg (co-chair)
Didier El Baz, team CDA, LAAS-CNRS, France (co-chair)
El-Ghazali Talbi, University of Lille, INRIA, CNRS, France
Albert Y. Zomaya, The University of Sydney, Australia


General Chairs:
===
Grégoire Danoy, University of Luxembourg, Luxembourg
Didier El Baz, team CDA, LAAS-CNRS, France


Program Chairs:
===
Vincent Boyer, University of Nuevo Leon, Mexico
Bernabe Dorronsoro, Universidad de Cádiz, Spain


Publicity Chairs:
=
Keqin Li, State University of New York at New Paltz, USA
Laurence T. Yang, St Francis Xavier University, Canada


Program Committee (to be confirmed):

A. Bendjoudi, CERIST, Algiers, Algeria
J.-N. Cao, Hong-Kong Polytechnic University, China
J. J. Durillo, Leibniz Supercomputer Center, Munich, Germany
S. Fujita, Hiroshima University, Japan
M. Halappanavar, Pacific Northwest National Laboratory, USA
K. Li, State University of New York, USA
N. Melab, University of Lille, France
M. Menai, King Saud University, Saudi Arabia
A. Nakib, University Paris 12, France
S. Nesmachnow, Universidad de la República, Uruguay
S. Nikoletseas, University of Patras and CTI, Greece
C. Phillips, Sandia National Laboratories, USA
T. Saadi, University of Picardie, France
M. Seredynski, Luxembourg Institute of Science and Technology, Luxembourg
G. Ch. Sirakoulis, Democritus University of Thrace, Greece
G. Spezzano, University of Calabria, Italy
A. Tchernykh, CICESE Research Center, Mexico
S. Varrette, University of Luxembourg, Luxembourg
F. Xhafa, Polytechnic University of Catalonia, Spain
L.T. Yang, St Francis Xavier University, Canada


Submission :

Papers in the Proceedings of the workshops will be indexed in the IEEE Xplore 
Digital Library after the conference.
Prospective authors should submit their papers through Workshop PDCO 2021 
submission system: 
https://ssl.linklings.net/conferences/ipdps/?page=Submit=PDCOWorkshopFullSubmission=ipdps2021


Abstract and paper can be uploaded until January 31, 2021. Authors should 
preferably follow the manuscript specifications  of IEEE IPDPS, i.e. 

[UAI] Doctoral Symposium - CISTI 2021, Chaves, Portugal

[Maria Lemos]

--  --  
--  --
Doctoral Symposium

CISTI 2021 - 16th Iberian Conference on Information Systems and Technologies, 
Chaves, Portugal, 23 - 26 June 2021

http://www.cisti.eu/ 

--  --  
--  -


The purpose of CISTI'2021’s Doctoral Symposium is to provide graduate students 
a setting where they can, informally, expose and discuss their work, collecting 
valuable expert opinions and sharing new ideas, methods and applications. The 
Doctoral Symposium is an excellent opportunity for PhD students to present and 
discuss their work in a Workshop format. Each presentation will be evaluated by 
a panel composed by at least three Information Systems and Technologies experts.



Contributions Submission

The Doctoral Symposium is opened to PhD students whose research area includes 
the themes proposed for this Conference. Submissions must include an extended 
abstract (maximum 4 pages), following the Conference style guide. All selected 
contributions will be published with the Conference Proceedings in electronic 
format with ISBN. These contributions will be available in the IEEE Xplore 
Digital Library and will be sent for indexing in ISI, Scopus, EI-Compendex, 
INSPEC and Google Scholar.

Submissions must include the field, the PhD institution and the number of 
months devoted to the development of the work. Additionally, they should 
include in a clear and succinct manner:

   •The problem approached and its significance or relevance
   •The research objectives and related investigation topics
   •A brief display of what is already known
   •A proposed solution methodology for the problem
   •Expected results



Important Dates

Paper submission: February 14, 2021

Notification of acceptance: March 28, 2021

Submission of accepted papers: April 11, 2021

Payment of registration, to ensure the inclusion of an accepted paper in the 
conference proceedings: April 11, 2021



Organizing Committee

Álvaro Rocha, ISEG, Universidade de Lisboa

Francisco García-Peñalvo, Universidad de Salamanca



Scientific Committee

Francisco García-Peñalvo, Universidad de Salamanca (Chair)

A. Augusto Sousa, FEUP, Universidade do Porto

Adérito Fernandes-Marcos, Universidade Aberta

Adolfo Lozano Tello, Universidad de Extremadura

Alicia García Holgado, Universidad de Salamanca

Álvaro Rocha, ISEG, Universidade de Lisboa

Ana Amélia Carvalho, Universidade de Coimbra

António Palma do Reis, ISEG, Universidade de Lisboa

Arnaldo Martins, Universidade de Aveiro

Borja Bordel, Universidad Politécnica de Madrid

Bráulio Alturas, ISCTE - Instituto Universitário de Lisboa

Carina Soledad González, Universidad de La Laguna

Carlos Costa, ISEG, Universidade de Lisboa

Carlos Ferrás Sexto, Universidad de Santiago de Compostela

Cesar Collazos, Universidad del Cauca

Daniel Amo, La Salle, Universidad Ramon Llull

David Fonseca, La Salle, Universitat Ramon Llull

Eduardo Sánchez Vila, Universidade de Santiago de Compostela

Fernando Moreira, Universidade Portucalense

Fernando Ramos, Universidade de Aveiro

Francisco Restivo, Universidade Católica Portuguesa

Gonçalo Paiva Dias, Universidade de Aveiro

João Costa, Universidade de Coimbra

João Manuel R.S. Tavares, FEUP, Universidade do Porto

João Pascoal Faria, FEUP, Universidade do Porto

José Machado, Universidade do Minho

Luis Camarinha-Matos, FCT, Universidade NOVA de Lisboa

Luís Paulo Reis, FEUP, Universidade do Porto

Marcelo Marciszack, Universidad Tecnológica Nacional

Marco Painho, NOVA IMS

María J Lado, Universidade de Vigo

María Pilar Mareca Lopez, Universidad Politécnica de Madrid

Mário Piattini, Universidad de Castilla-La Mancha

Martin Llamas Nistal, Universidad de Vigo

Miguel de Castro Neto, NOVA IMS

Miguel Ramón González-Castro, ENCE

Nelson Rocha, Universidade de Aveiro

Óscar Mealha, Universidade de Aveiro

Paulo Pinto, FCT, Universidade Nova de Lisboa

Ramiro Gonçalves, Universidade de Trás-os-Montes e Alto Douro

Tomas San Feliu, Universidad Politécnica de Madrid

Vitor Santos, NOVA IMS



Website of CISTI'2020: http://www.cisti.eu/ 



CISTI 2021 Team

http://www.cisti.eu/ 


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[UAI] Call for papers "Measures of Dependence in Machine Learning and Signal Processing" (Special issue Entropy - MDPI) Deadline May 31st, 2021

[Sanchez Giraldo, Luis G.]

Special Research topic in Entropy. Guest editor: Luis Gonzalo Sanchez Giraldo 
(University of Kentucky)


Title:  “Measures of Dependence in Machine Learning and Signal Processing.”


Researchers are invited to submit papers for this special edition.

For more information about this call for papers visit URL:

https://www.mdpi.com/journal/entropy/special_issues/Measures_Dependence



Submission deadline: May 31, 2021



The aim of this special issue is to collect promising, recent, and novel 
research developments in measures of dependence in machine learning and signal 
processing.

Areas to be covered in this Research Topic may include, but are not limited to:

  *   New measures of dependence for high dimensional data.

  *   Theory of estimators of dependence

  *   New applications.

For questions, please contact Prof. Luis Gonzalo Sanchez Giraldo via email: 
luis.sanc...@uky.edu

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[UAI] 16th International Computer Science Symposium in Russia (CSR 2021): Call for Papers

[Alexander Kulikov]

We apologize for multiple copies.

***

Second Call for Papers

16th INTERNATIONAL COMPUTER SCIENCE SYMPOSIUM IN RUSSIA (CSR 2021)

June 28-July 2, 2021, Sochi, Russia

https://logic.pdmi.ras.ru/csr2021/

***

CSR is an annual international conference held in Russia that is
designed to cover a broad range of topics in Theoretical Computer
Science. The list of previous CSR conferences can be found at
https://logic.pdmi.ras.ru/~csr/ . Conference proceedings are published
in Springer's Lecture Notes in Computer Science series.

IMPORTANT DATES

Deadline for submissions:   December 24, 2020
Notification of acceptance: February 8, 2021
Conference dates:   June 28-July 2, 2021

TOPICS
include, but are not limited to:

(i) algorithms and data structures
(ii) computational complexity, including hardness of approximation and 
parameterized complexity 
(iii) randomness in computing, approximation algorithms, fixed-parameter 
algorithms
(iv) combinatorial optimization, constraint satisfaction, operations research
(v) computational geometry
(vi) string algorithms
(vii) formal languages and automata, including applications to computational 
linguistics
(viii) codes and cryptography
(ix) combinatorics in computer science
(x) computational biology
(xi) applications of logic to computer science, proof complexity
(xii) database theory
(xiii) distributed computing
(xiv) fundamentals of machine learning, including learning theory,   
grammatical inference and neural computing
(xv) computational social choice
(xvi) quantum computing and quantum cryptography
(xvii) theoretical aspects of big data


OPENING LECTURE

Tim Roughgarden (Columbia University, USA)

INVITED SPEAKERS

TBD

PROGRAM COMMITTEE

Rahul Santhanam (University of Oxford, UK; Chair)
Elena Arseneva (St. Petersburg State Univesity, Russia)
Alexander Belov (University of Latvia, Latvia)
Simina Branzei (Purdue University, USA)
Andrei Bulatov (Simon Fraser University, Canada)
Anupam Das (University of Birmingham, UK)
Laure Daviaud (City University of London, UK)
Laurent Doyen (LSV - ENS Paris-Saclay, France)
Piotr Faliszewski (AGH University of Science and Technology, Poland)
Pawel Gawrychowski (University of Wroclaw, Poland)
Heng Guo (University of Edinburgh, UK)
Siyao Guo (NYU Shanghai, China)
Shuichi Hirahara (NII, Japan)
Mikhail Kapralov (EPFL, Switzerland)
Jesper Nederlof (Utrecht University, Netherlands)
Alexander Okhotin (St. Petersburg State University, Russia)
Sofya Raskhodnikova (Boston University, USA)
Alexander Razborov (University of Chicago, USA)
Suzanna de Rezende (Czech Academy of Sciences, Czech Republic)
Laura Sanita (University of Waterloo, Canada)
Kavitha Telikepalli (TIFR, India)
Amir Yehudayoff (Technion, Israel)
Meirav Zehavi (Ben-Gurion Ubiversity, Israel)


SUBMISSIONS

Authors are invited to submit an extended abstract or a full paper of at most
12 pages in English, not including references, in the LNCS format (LaTeX, as 
pdf; final 
version with source); instructions are here:
https://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines
   
Proofs and other material omitted due to space constraints are to be put into
a clearly marked appendix to be read at discretion of the referees. Papers
must present original (and not previously published) research. Simultaneous
submission to journals or to other conferences with published proceedings is
not allowed.  The proceedings of the symposium will be published in Springer's
LNCS series.

Submissions by PC members will be allowed but will be held to a higher standard 
than non-PC submissions.

Submission server: https://easychair.org/conferences/?conf=csr2021

We are carefully watching the situation with the Covid-19 pandemic. We hope to 
conduct a physical event, but it will be possible to participate in the event 
online for those who are unable to come due to travel restrictions or other 
circumstances. In case the situation in Russia does not allow us to organize 
a meeting in place, we are planning to move the event online 
but not to postpone it.

FURTHER INFORMATION AND CONTACTS

Web:http://logic.pdmi.ras.ru/csr2021/
Email:  musatov...@phystech.edu


UNSUBSCRIPTION: If you do not wish to receive any news 
regarding CSR conferences, please reply to this mail
and we will remove you from the mailing list.
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[UAI] AAMAS 2021: 2dn Call for Doctoral Consortium papers

[AAMAS2021 Publicity Chair]

AAMAS 2021 invites submissions to the Doctoral Consortium.

The doctoral consortium (DC) of AAMAS 2021 is intended to provide Ph.D.
students the opportunity (1) to receive feedback on their research (from
established researchers in their fields), (2) to interact closely with
established researchers/mentors, and (3) to build their professional
network.

Each accepted student to the program will be matched with an established
researcher/mentor in the field who will assist the student with research
and career management advice. An informal lunch will be organized between
the students and their mentors allowing for in-depth discussion and
exchange.

Important Dates
- Submission Deadline: January 5 (23:59 UTC-12)
- Author Notification: February 5 (23:59 UTC-12)
- Camera Ready Deadline: March 5 (23:59 UTC-12)
- Doctoral Consortium: May 3 – 4

For further details and submission instructions, please visit:
https://aamas2021.soton.ac.uk/calls/call-for-doctoral-consortium-applications/
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[UAI] PhD student position, University of Geneva (CS) and University of Applied Sciences

[Kalousis Alexandros (HES)]

We have an opening for a PhD position. The research target is the 
development of deep generative models that can incorporate strong domain 
knowledge within the learning process. Such domain knowldege, typically 
available in scientific fields, can be encoded in various forms such as 
equation-based models (e.g. physics and chemistry), simulators (e.g. 
biomechanical models), and more general black-box programming artifacts 
(chemoinformatics RDKit). Eventually such models should be considerably 
more data efficient and offer additional advantages in terms of 
interpretability.

The successful candidate will enroll as a PhD student in the Computer 
Science department of the University of Geneva (under the co-direction 
of myself and Prof. Stephane Marchand-Maillet) and, at the same time, 
will become a member of the Data Mining and Machine Learning group 
(http://dmml.ch) at the University of applied sciences, Geneva. The 
position shall be filled in as soon as possible.

We seek strongly motivated candidates prepared to dedicate to high 
quality research. The candidate should have (or be close to obtaining) a 
Master's degree or equivalent in computer science, statistics, applied 
mathematics, electrical engineering or other related field with strong 
background in machine learning and programming (Pytorch and/or Tensorflow).

If interested, please send the following to alexandros.kalou...@hesge.ch
- academic CV (max 2 pages)
- academic transcripts of BSc and MSc
- one page motivation letter explaining why the candidate is suitable 
for the position
- 500 word research proposal on one of the topics described above
- contact details of three referees (do not send reference letters)

Deadline for applications: 31/12/2020.

In case of any further questions, please contact 
alexandros.kalou...@hesge.ch.

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