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🔹در مسیر اپلای از آغاز تا پرواز در کنار شما هستیم

🔸ارتباط با ما:
@Dr_Apply

کانال پوزیشن‌ها:
@ApplyTime_Positions

پرداخت ارزی:
@Pay_Time
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PhD candidates in the AI for Healthcare

PhD candidates in the computer vision area

@ApplyTime
🌎 #اپلای

🚩 با اپلای تایم می‌تونید به پوزیشن‌های مختلف تحصیلی به صورت رایگان دسترسی داشته باشید و در گروه پرسش و پاسخ تمام فرآیند اپلای رو مستقیما از مشاوران ما و سایر دانشجویان پرس و جو کنید.

🌜🌛 TimeToTalk group: https://news.1rj.ru/str/+lqOevs8uSjgxNmZk

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Forwarded from Vahooman Deutschlehrer
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Postdoctoral Fellow Position at Carnegie Mellon University
Deep Reinforcement Learning Techniques for Human Robot Teaming Systems
OPEN POSITION: A postdoctoral fellow position at Robotics Institute,
CMU SUPERVISOR:
Prof. Katia Sycara (katia@cs.cmu.edu)
The Robotics Institute, Carnegie Mellon University
Website: http://ri.cmu.edu/ri-faculty/katia-sycara
LOCATION:
The Advanced Agent-Robotics Technology Lab
The Robotics Institute,
Carnegie Mellon University
Pittsburgh, Pennsylvania, USA
DESCRIPTION: The successful candidate will work on Deep Reinforcement Learning algorithms for human agent teams, with agents interacting autonomously or with humans. Position open immediately in 2022. Start in early 2023 is negotiable. The expected duration of the position is one to three years with renewals upon review. In particular, the research will involve computational models for making inferences and predictions about the behaviors and activities of other agents and human-agent teams so as to (1) perform complementary beneficial actions, and (2) give advice to human and agent team mates to improve overall team performance. The research involves a rich variety of research issues, such as theory of mind models, explainable AI, concept learning and transfer learning.
QUALIFICATIONS: - PhD in a field related to AI/ML in particular reinforcement learning in Robotics, CS or related discipline.
- A strong theoretical background in Machine Learning
- Programming skills including experiences using C++, Python, and/or MATLAB, Neural Network frameworks, eg pytorch
- Ability to present work clearly both written and orally
- Experiences with deep learning tools mandatory.
APPLICATION DETAILS: Applicants should provide the following material via email to Prof. Katia Sycara (katia@cs.cmu.edu). Please use the subject line: “Postdoc application”. Applications will be reviewed as they are received. - A curriculum vitae - A statement of research expertise and interests (up to 2 pages) - Up to 3 publications - Names and contact information of three references - Dates of availability - A personal website, if available, where further details can be found
DUTIES AND RESPONSIBILITIES
The postdoc will (a) carry out high quality research and publish the research results, (b) assist in research supervision and guidance of graduate and undergraduate students, (c) present research results to sponsors, (d) participate in research proposal preparation.

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شاید در طول روز به پوزیشن‌های زیادی برخورد می‌کنین که مناسب خود شما نیست اما احتمالا مناسب دانشجویان دیگه هست. گروه زیر جائیه که شما می‌تونین این دسته از پوزیشن‌ها رو به اشتراک بذارین و به باقی دانشجویان کمک کنین. طبیعتا اگه دیگران هم این کار رو انجام بدن،‌ کمک بزرگی برای شما خواهد بود. پس با به اشتراک‌گذاری پوزیشن‌هایی که بهشون نیازی نداریم، به دیگران و خودمون کمک کنیم.

لینک عضویت در گروه:

https://news.1rj.ru/str/time_to_share_open_positions

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Attached are two Calls for Applications for my new team at Münster University’s Geography Department. — Please feel free to share widely, I’m very keen on receiving international applications! 


https://www.uni-muenster.de/Rektorat/Stellen/ausschreibungen/st_20220107_sk13.html

https://www.uni-muenster.de/Rektorat/Stellen/ausschreibungen/st_20220107_sk12.html


Many thanks and best wishes,

Sarah
UNIVERSITY OF LEIPZIG


Dr Sarah Ruth Sippel

Institute of Cultural Anthropology

Schillerstr. 6

04109 Leipzig, Germany

+49 (0) 34 1973 7223
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2022-05132 - Post-Doctoral Research Visit F/M Energy-Aware Federated Learning, Inria, France

2022-05159 - Post-Doctoral Research Visit F/M Federated Learning in Healthcare (FLH): Analysis of Multicentric Hospital Data, Inria, France

2022-05068 - Post-Doctoral Research Visit F/M Post doctoral fellow in computer vision / deep learning: deepfake detection, Inria, France

2022-05117 - Post-Doctoral Research Visit F/M Reinforcement Learning with Applications to Active Learning and Recommender Systems, Inria, France

2022-05156 - Post-Doctoral Research Visit F/M Fair and Optimal Design of (Repeated) MarketPlace, Inria, France

2022-05170 - Inria and InterDigital - Haptic “super-powers” for improving the exploration of metaverse, Inria, France

2022-05163 - Post-Doctoral Research Visit F/M - Inria and InterDigital - Deep-based semantic representation of avatars for virtual reality, Inria, France

2022-04801 - Post-Doctoral Research Visit F/M Modeling of photoplethysmography measurement and estimation of blood pressure, Inria, France

2022-04862 - Post-Doctoral Research Visit F/M Postdoc Position F/M [2 years: 3D Transformers for Autonomous Driving, Inria, France](https://news.1rj.ru/str/ApplyTimePositions/16983)

[2022-05105 - Post-Doctoral Research Visit F/M Emissions mapping & analysis of a geo-distributed computing infrastructure in comparison to centralised architectures, Inria, France](
https://news.1rj.ru/str/ApplyTimePositions/16984)

If you are not interested in these positions, share them with your friends. You might change their life by simply sharing these!

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🌐 https://applytime.ir
A fully-funded 3.5 year PhD project is available in the Mark Humphries’ lab at the University of Nottingham, UK.



Broad classes of network models, like small-world networks and scale-free networks, have taught us much about the world. But we suspect a major class of networks has been missed. This project will introduce and explore a new class of model weighted networks, “divergent” networks, in which the structure described by the links and their weights do not match. Most theoretical work on weighted networks assumes that they do, so little is known about the properties of these divergent networks. We will close that gap by quantifying the existence and extent of divergence in a range of real-world networks, including brain connectomes at both single neuron and inter-area level; by creating generative models for these networks; and by exploring how divergence alters a network’s dynamics across a range of dynamical systems implemented on the nodes, including neural models.



The student will be joining the Humphries lab (https://www.humphries-lab.org/), who draw on network theory and dynamical systems approaches to understand neural coding and computations. They will also be co-supervised by Prof Stephen Coombes (School of Maths), an expert in dynamics on networks.



Suggested reading:

Humphries, M. D., Caballero, J. A.*, Evans, M.*, Maggi, S.* & Singh, A.* (2021) Spectral estimation for detecting low-dimensional structure in networks using arbitrary null models. PLoS ONE, 16(7): e0254057.



Enquiries: mark.humphries@nottingham.ac.uk (send a CV with queries please)



Application deadline: July 29th 2022



Further details, and how to apply: https://www.findaphd.com/phds/project/divergent-networks-a-new-class-of-complex-systems/?p145584



Funding information:

EPSRC DTP studentship, 3.5 years duration.

Start: October 2022

Studentship will pay Home (UK) University tuition fees (minimum £4,596 per year) and a minimum stipend of £16,062 per year for your living costs. International students are welcome to apply, but note the studentship does not cover international tuition fees (currently £26,000 per year).



Professor Mark Humphries | Professor of Computational Neuroscience


My book "The Spike: An Epic Journey Through the Brain in 2.1 Seconds" is out now in hardback, ebook, and audiobook! https://press.princeton.edu/books/hardcover/9780691195889/the-spike

Lab: humphries-lab.org

Twitter: @markdhumphries

Public blog: https://medium.com/the-spike
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