💻 یادگیری بدون نظارت (Unsupervised Learning) چیست؟

🗒 یادگیری بدون نظارت، از الگوریتم های یادگیری ماشین برای تجزیه و تحلیل و خوشه بندی مجموعه داده های بدون برچسب استفاده می کند. این الگوریتم ها الگوهای پنهان یا گروه بندی داده ها را بدون نیاز به دخالت انسان کشف می کنند.

💻 رگرسیون خطی با یک متغیر

🗒 رگرسیون خطی با یک متغیر زمانی استفاده می‌شود که بخواهید یک مقدار خروجی را از یک مقدار ورودی پیش‌بینی کنید. یعنی شما فقط یک x به عنوان ورودی و یک y به عنوان خروجی دارید.

🔻گفتگوی الهام بخش با دکتر بابك خلج، رئیس دانشکده مهندسی برق در دانشگاه صنعتی شریف و مدیر مرکز سیستم های اطلاعات و علوم داده شريف. در اين گفتگو، به داستان زندگی و دیدگاه ايشان برای مرکز علوم داده می پردازیم. این مصاحبه، نگاهی منحصر به فرد به داستان زندگى یک شخصیت پیشرو علمی ارائه می دهد.

👨‍🎓میزبان: دكتر وصال احسنى، پژوهشگر پسادکتری دانشکده مهندسی برق در دانشگاه صنعتی شریف و مرکز سیستم های اطلاعات و علوم داده.

🔻جهت مشاهده این ویدیو می توانید از لینک های آپارات و یوتیوب هم استفاده کنید:
Youtube | Aparat
🔻 جهت دنبال کردن اخبار مربوط به مرکز سیستم های اطلاعات و علوم داده شریف هم می توانید از لینک های زیر استفاده کنید
Website | LinkedIn

⭕️ کتاب
Machine learning for healthcare application

🔰 ناشر: Wiley
🔰 تاریخ انتشار: 2022

🔰 این کتاب به صورت کلی به کاربردهای بسیار مختلف حال حاضر یادگیری ماشین در سلامت، تشخیص و درمان بیماری‌های مختلف می‌پردازد.

🔰 این کتاب، مجموعه‌ای از کاربردها و پژوهش‌ها در بحث تشخیص تصاویر پزشکی و تحلیل داده‌های تصویری تا کاربرد اینترنت اشیا و همچنین کاربرد در جریان پاندمی کرونا را به تصویر می‌کشد.

🔰 همچنین، این کتاب حوزه‌های مختلفی را پوشش داده است و می‌تواند به محققین و دانشجویان جهت آشنایی کاربردهای وسیع یادگیری ماشین و روش تحقیق در آن حیطه‌ها یاری برساند.

🔰 این کتاب مروری بر پژوهش‌های صورت گرفته در تشخیص بیماری‌های پیش‌رونده از جمله مالاریا با روش‌های معمول یادگیری ماشین و در ادامه کاربرد انواع شبکه‌های عصبی، پردازش سیگنال‌های مغزی و پیچیدگی‌های به کارگیری هوش مصنوعی در بالین، به صورت مختصر دارد.

🔰 همچنین، اشاره‌ای نیز به اینترنت اشیا و کاربرد آن به همراه یادگیری ماشین در پیاده‌سازی نظام سلامت جامع و یکپارچه و نظام نظارت بر سازمان می‌کند.

⭕️ ۲۰ ابزار برتر هوش مصنوعی برای دانشمندان داده 2023

🔷 ابزارهای پیشرفته هوش مصنوعی پروژه های علم داده را متحول می کنند. از H2O.ai گرفته تا PyTorch، این ابزارهای منحصر به فرد آینده تحلیل داده ها و یادگیری ماشین را شکل می دهند.

🔺 در فایل فوق ۲۰ ابزار برتر AI که می‌تواند آنالیز داده‌ها و ساخت و مدل های یادگیری ماشین را متحول کند معرفی شده است. از بقیه جلوتر باشید و قدرت هوش مصنوعی را در پروژه های داده محور خود اعمال کنید.

📚 The Doctor and the Algorithm

🖇 The Doctor and the Algorithm combines insights from science and technology studies, critical algorithm studies, and public interest informatics to better understand the promise and peril of health AI. The book draws on case studies in automated diagnostics, algorithmic pain measurement, AI-driven drug discovery, and death prediction to investigate how health AI is made, promoted, and justified. It explores the enthusiastic promises of health AI marketing communication and medical futurism while also analyzing the inequitable outcomes new AI technology often creates for already marginalized communities. Finally, the book closes with specific recommendations for regulatory frameworks that might support more ethical and equitable approaches to health AI in the future.

📚 فایل نسخه epub کتاب ارزشمند The Doctor and the Algorithm

با ما در مسیر آینده همراه باشید 🌱

🎯 یادگیری ماشین چگونه مراقبت های سلامت را بهبود می بخشد؟

🔺دکتر مرضیه قاسمی، استاد دانشگاه MIT

🔝 TED talk by Dr. Marzyeh Ghassemi, Assistant Professor at MIT

🔺کاربردهای هوش مصنوعی در پزشکی و سلامت

مدرس: دکتر مهدی سعادتی، دکترای هوش مصنوعی

عنوان مقاله:

3D-Printed microfluidic device for protein purification in batch chromatography

عنوان مقاله:

3D-Printed microfluidic device for protein purification in batch chromatography

موقعیت دکتری کامپیوتر
انگلیس

a PhD student to work on structured generative
models of images and videos, in the School of Computing Science at the
University of Glasgow.

Possible research topics include:
- deep generative models of images that represent their latent 3D structure
- structured models for video incorporating physical knowledge
- object-centric and compositional generative models
- structured generative models for medical imaging data

You should have a good degree in computer science / maths / similar,
and excellent coding skills. Funding is available for strong
candidates; the starting date is January 2024 (with some flexibility).

Please contact me directly (via paul.henderson@glasgow.ac.uk) before
applying, to discuss suitability and negotiate a research topic.
Include your CV, transcripts, and a short (one page) research
proposal. The deadline for informal applications is 17th July.

The University of Glasgow (est. 1451) is a member of the UK's Russell
Group of leading research universities. It is ranked 5th in the U.K.
for computer science [Times Good University Guide 2022]. The School of
Computing Science has over 70 faculty, and over 130 research students.
The School particularly encourages applications from groups who are
traditionally under-represented in computer science.

Best regards,

Dr. Paul Henderson

Assistant Professor (Lecturer)
School of Computing Science
University of Glasgow
https://www.pmh47.net

موقعیت دکتری فول فاند
هلند

We invite applications from enthusiastic candidates interested in joining us as a full-time PhD researcher in the field of Reinforcement Learning (broadly speaking) within the Uncertainty in AI group at TU Eindhoven, in the Netherlands.

Reinforcement Learning is a dynamic and versatile area with a wide range of applications. As a PhD researcher in our group, you will have the chance to explore different approaches, algorithms, and techniques in this field including their integration with uncertainty-aware and robust methodologies. 

The position is fully funded, and we offer competitive salaries. We warmly welcome international candidates, as knowledge of the Dutch language is not required.

To learn more about the specific requirements and application process, please visit the following link:
https://jobs.tue.nl/en/vacancy/phd-position-in-reinforcement-learning-990306.html

We look forward to receiving your applications to review. The vacancy will remain open until the position is filled.

Kind regards,
Maryam
https://maryamtavakol.com/

چندین موقعیت دکتری کامپیوتر

انگلستان

doctoral students in the Intelligent Robotics Lab (IRLab) within the School of Computer Science at University of Birmingham (UK).

This position will focus on fundamental research at the intersection of knowledge representation (KR) and robot manipulation. I am looking for candidates with:

* An excellent undergraduate or Masters degree in a computing discipline, e.g., computer science, engineering, mathematics, or physics.
* Demonstrated understanding of the fundamentals of robot control and KR, e.g., performance in a related undergraduate or Masters-level module.
* Demonstrated proficiency in object-oriented programming.
* Expertise/interest in working with physical robot platforms.
* (Preferred) Prior research experience in robotics or AI.

These positions cover tuition fees and provide a monthly stipend.

Please contact me (m.sridharan@bham.ac.uk) with a link to a folder with your application material (e.g., research proposal, transcripts, CV) if you would like to have an informal chat.

Regards,
--Mohan
https://www.cs.bham.ac.uk/~sridharm


@safarname7

موقعیت دکتری چهارساله فول فاند

سوییس
The People-Centered Computing Lab in the Faculty of Informatics at the Università della Svizzera italiana (USI) in Lugano, Switzerland, is looking for a candidate for a 4-year PhD-student position in machine learning (ML). The position is funded by an SNF Ambizione project. Dr. Martin Gjoreski and Prof. Marc Langheinrich will be the co-supervisors. The project includes collaborations with leading research groups from MIT (US), Cambridge (UK), Melbourne (AU), and UNIGE (CH). As part of the project, the Ph.D. student will work on the development of novel methods for “Privacy-aware domain adaptation.” 
The Ph.D. position is full-time, with a competitive salary and social security insurance. Per Swiss regulations, Ph.D. student salaries range from CHF 47'040 (gross) in the first year to CHF 50'040 (gross) in the last year. Apart from performing research, the faculty’s Ph.D. program also expects students to complete coursework and acquire teaching experience.
Application deadline: 1st September 2023 (envisioned project start: 1st January 2024). Notifications will be sent by the 29th of September, 2023. For more information, please check: https://pc.inf.usi.ch/uncategorized/ph-d-position-on-privacy-aware-domain-adaptation-in-affective-and-wearable-computing-in-lugano-switzerland-application-deadline-september-1-2023/

موقعیت دکتری فول فاند
فنلاند

The Robot Learning research group is seeking a talented PhD student with strong interest in Multi-agent Reinforcement Learning and Planning.

The Aalto Robot Learning research group operates in the intersection of artificial intelligence and robotics. We focus on developing methods for reinforcement learning, robotic manipulation, decision making under partial observability, imitation learning, and decision making in multi-agent systems. The goal of the research group is to help robots understand what they need to learn to perform their assigned tasks, and, thus, make robots capable of operating on their own and pro-actively help humans. To accomplish these goals the research group develops novel decision making methods and uses these methods to solve unsolved robotic tasks. For more information, please see https://rl.aalto.fi

The main task of the PhD student will be to develop new methods for optimizing multi-agent behavior. The developed methods may be based on one of our focus areas including, but not limited to, reinforcement learning and planning under uncertainty. Example research topics include but are not limited to multi-agent curriculum learning, model-based multi-agent reinforcement learning, and multi-agent planning and control. The developed methods may be evaluated with real robots. The exact direction of the research is chosen depending on your experience and interests. Please relate clearly to some of the research topics in your Letter of Motivation.

Outstanding researchers from the areas of Machine Learning, AI, Robotics, and related areas including Reinforcement Learning, Control Engineering, Computer Vision, Statistics & Optimization, or Mathematics & Physics are welcome to apply. The candidate is expected to conduct independent research and at the same time contribute to the topics listed above. Successful candidates will be furthermore given the opportunity to work with undergraduate and M.Sc. students.

The research group collaborates internationally and nationally with research groups in construction, computer vision, robotics, mobile heavy machines, human-robot interaction, reinforcement learning, imitation learning, multi-agent systems, under-water vehicles, and robot motion planning. There will be ample opportunities for international collaboration.

WE OFFER

The position will be filled for 2 + 2 years (doctoral studies are expected to take 4 years in total). The starting date is in September 2023 or as mutually agreed. The salary will be based on both the job requirements and the employee’s personal performance in accordance with the salary system of Finnish universities. The starting salary for a doctoral student is approximately 2600 EUR/month and increases with thesis progress.

We offer a wide range of staff benefits, such as occupational health care, flexible working hours, excellent sports facilities on campus and several restaurants and cafés on campus with staff discounts. The position is located at the Aalto University Otaniemi campus which can be easily reached by public transport.

HOW TO APPLY

Please submit your application through our online recruitment system at
https://www.aalto.fi/en/open-positions/phd-student-position-in-multi-agent-reinforcement-learning-and-planning
(on the web page scroll down and click the "Apply Now!" button)

The closing date for applications is August 27th, 2023 (23:59 EEST (GMT+3)).
Please write your application and all the accompanying documentation in English and attach them in PDF format. Please attach only the following documents to your application:
* A letter of motivation describing your research interests and how the research fits to the Robot Learning research group (max. 1 page)
* Curriculum vitae (including the contact details of two referees)
* A list of publications as a part of the curriculum vitae

* PDF copy of your MSc and BSc degree certificates, including transcripts of all MSc and BSc university records (grades and courses) and their English translations (Finnish and Swedish certificates are also accepted)

Please note that our recruitment system allows max 5 attachments, so please combine the copies of certificates and transcripts in one PDF, if necessary.

ADDITIONAL INFORMATION

For further information, please contact Assistant Professor Joni Pajarinen, joni.pajarinen@aalto.fi. Additional information in recruitment process related questions, please contact HR Coordinator Camilla Hanganpää, camilla.hanganpaa@aalto.fi.