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سلام دوستان، این پیام را یکی از دوستانم فرستاده، اگر کسی با این شرایط می شناسید تا بهش معرفی کنیم.
Hi. I can find a PhD student.
If you know strong master students who interested to do his PhD in England plz share his resume and potential proposals to interview.
Also the proposal needs to related to 5G if possible.
University of surrey, Guildford, England
Hi. I can find a PhD student.
If you know strong master students who interested to do his PhD in England plz share his resume and potential proposals to interview.
Also the proposal needs to related to 5G if possible.
University of surrey, Guildford, England
Forwarded from Apply Now
PhD Student Position for the topic “self-organized collective patterns on graphs
#دکترا
#آلمان
Jacobs University is a private, state-accredited, English-language research university in Bremen. We are offering PreDegree, Bachelor, Master or PhD programs in three focus areas: Health, Mobility and Diversity and are involved in the professional development of specialists and managers and in the transfer of knowledge. Our principles are first class research and teaching, international diversity and transdisciplinary cooperation. As an international university we attract highly talented and open-minded students from all over the world. Currently, more than 1,400 students from 110 nations live and study on our residential campus.
The department „ Life Sciences & Chemistry” invites interested candidates to apply for the next possible date for a
PhD Student Position for the topic “self-organized collective patterns on graphs” (m/f/d)
(Full-time, Start February 2020, limited for 3 years)
Job ID 19 -78
PhD Research project
The relationship between network architecture and dynamics is often assessed on a link-by-link level, e.g., evaluating pairwise correlations among nodes and comparing them with the set of links in a network.
Over the last few years, however, diverse studies have established that many forms of dynamics self-organize on networks to give rise to large-scale collective patterns. The dynamical pattern is then a consequence of the parameters defining the dynamics as well as the network architecture. Examples include Turing patterns on graphs arising from reaction-diffusion systems, self-organized waves around hubs arising in excitable dynamics and synchronization of modules arising in coupled oscillators. These self-organized, collective behaviours are in the focus of this computational project.
This project will employ numerical simulations of simple dynamical processes on graphs to better understand and classify such collective patterns in networks. Based on these theoretical investigations, the relevance of such patterns to the diverse application domains in the ITN will be assessed and the findings will be validated using the rich data resources of the ITN.
Context:
This research fellowship programme (PhD) will be carried out within the context of the i-CONN network, a Marie Skłodowska-Curie Actions– Innovative Training Network (ITN) – project funded by the European Commission, under their H2020 program. Through the project activities, the Fellows/PhD students will have the opportunity to come in contact and collaborate with some of the best European research groups. English is the official language of the i-CONN project. Additional details are available in “Further particulars”.
Your research responsibilities:
Perform high quality research in the bespoke research project under the guidance of the supervisory team.
Meet the members of the supervisory team on a regular basis.
Participate in the activities of the Network as specified in the Grant Agreement and/or required by the node coordinator, including secondments in other network nodes and taking part in the network meetings and in the training activities.
Write up the results of the research activity and present research papers and publications at meetings and conferences, as advised by the supervisors, and contribute to the overall goals of the network.
Widen the personal knowledge in the research area and undertake complementary training.
Keep records of the activities, such as research, training, secondments, visits, leave of absence, etc.
Your qualifications:
The successful candidates must satisfy the eligibility criteria (see below) and have:
An excellent academic record in a quantitative discipline, including, but not restricted to: Computational Systems Biology, Bioinformatics, Statistical Physics, Data Science, Applied Mathematics, Computer Science or related areas.
A keen interest in pursuing research in the development of Connectivity Science.
The ability to work independently and as a member of a rese
#دکترا
#آلمان
Jacobs University is a private, state-accredited, English-language research university in Bremen. We are offering PreDegree, Bachelor, Master or PhD programs in three focus areas: Health, Mobility and Diversity and are involved in the professional development of specialists and managers and in the transfer of knowledge. Our principles are first class research and teaching, international diversity and transdisciplinary cooperation. As an international university we attract highly talented and open-minded students from all over the world. Currently, more than 1,400 students from 110 nations live and study on our residential campus.
The department „ Life Sciences & Chemistry” invites interested candidates to apply for the next possible date for a
PhD Student Position for the topic “self-organized collective patterns on graphs” (m/f/d)
(Full-time, Start February 2020, limited for 3 years)
Job ID 19 -78
PhD Research project
The relationship between network architecture and dynamics is often assessed on a link-by-link level, e.g., evaluating pairwise correlations among nodes and comparing them with the set of links in a network.
Over the last few years, however, diverse studies have established that many forms of dynamics self-organize on networks to give rise to large-scale collective patterns. The dynamical pattern is then a consequence of the parameters defining the dynamics as well as the network architecture. Examples include Turing patterns on graphs arising from reaction-diffusion systems, self-organized waves around hubs arising in excitable dynamics and synchronization of modules arising in coupled oscillators. These self-organized, collective behaviours are in the focus of this computational project.
This project will employ numerical simulations of simple dynamical processes on graphs to better understand and classify such collective patterns in networks. Based on these theoretical investigations, the relevance of such patterns to the diverse application domains in the ITN will be assessed and the findings will be validated using the rich data resources of the ITN.
Context:
This research fellowship programme (PhD) will be carried out within the context of the i-CONN network, a Marie Skłodowska-Curie Actions– Innovative Training Network (ITN) – project funded by the European Commission, under their H2020 program. Through the project activities, the Fellows/PhD students will have the opportunity to come in contact and collaborate with some of the best European research groups. English is the official language of the i-CONN project. Additional details are available in “Further particulars”.
Your research responsibilities:
Perform high quality research in the bespoke research project under the guidance of the supervisory team.
Meet the members of the supervisory team on a regular basis.
Participate in the activities of the Network as specified in the Grant Agreement and/or required by the node coordinator, including secondments in other network nodes and taking part in the network meetings and in the training activities.
Write up the results of the research activity and present research papers and publications at meetings and conferences, as advised by the supervisors, and contribute to the overall goals of the network.
Widen the personal knowledge in the research area and undertake complementary training.
Keep records of the activities, such as research, training, secondments, visits, leave of absence, etc.
Your qualifications:
The successful candidates must satisfy the eligibility criteria (see below) and have:
An excellent academic record in a quantitative discipline, including, but not restricted to: Computational Systems Biology, Bioinformatics, Statistical Physics, Data Science, Applied Mathematics, Computer Science or related areas.
A keen interest in pursuing research in the development of Connectivity Science.
The ability to work independently and as a member of a rese
Forwarded from Apply Now
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Master Internship in Recognition of Sport Gestures with Hierarchical Deep NNs Research Internship proposal
🌐
https://news.1rj.ru/str/Apply_Now_Andishehsazan
🌐
https://news.1rj.ru/str/Apply_Now_Andishehsazan
Forwarded from Apply Now
Master research internship, Paris: Cross-lingual transfer with multi-lingual BERT via linguistically informed fine-tuning
Title: Cross-lingual transfer with multi-lingual BERT via linguistically informed fine-tuning
- Duration: 5-6 months, during the year 2020
- Location: LIMSI, Orsay (south of Paris)
- Supervisor: Caio Corro - http://caio-corro.fr/
- Team: Spoken Language Processing / Traitement Automatique de la Parole
- Contact: caio.corro@limsi.fr
Context
Recently, much attention has been paid to large scale pre-training of context-sensitive representations (or context-sensitive word embeddings), in particular ELMO [1] and BERT [2] models. The main idea is to pre-train the first layers of a neural network on a large amount of unlabeled data before fine-tuning the rest of the network on a downstream task. As such, context-sensitive representations allow to lower annotation cost and improve classification performance on a wide range of tasks.
The multilingual BERT model pre-trains context sensitive representations on a collection of texts in 104 languages instead of texts in a single language. One question that arises is whether we can use the multilingual BERT model for cross-lingual learning,
that is training a model on a subset of these languages (source languages) and testing it on a different subset (target languages). This problem is both important under a research perspective (how can we learn multi-lingual representations of typologically diverse languages?) and under an applied industry perspective (i.e. increase language coverage of NLP-based products at low cost). Previous work observed that cross-lingual transfert based on multi-lingual BERT works best for typological similar languages (i.e. languages with similar word order), which is expected but disappointing [3].
This internship will focus on multilingual dependency parsing with the Universal Dependency treebank https://universaldependencies.org/ . Previous work has considered re-ordering source language sentences with respect to word order in target languages [4]. However, re-ordering is not possible for unsupervised large scale pre-training where syntactic structures is not annotated. A different line of work proposed to force word order statistics at test time using constraints [5], but this method is based on a costly lagrangian optimization procedure and cannot be applied on a per sentence basis. Alternatively, we propose to explore fine-tuning methods for multi-lingual BERT model using a linguistically informed training algorithm, i.e. to use dominant word order information (is the object placed before or after the verb in a given language?) to ensure unsupervised transfer to target languages.
Missions
The successful candidate will develop neural network architectures and training algorithms for cross-lingual generalization of pre-trained context-sensitive representations. The main evaluation task will be cross-lingual dependency parsing. As there are many ways to tackle this problem, the specific approach will be determined by the intern aspiration, which could be for example posterior regularization or latent variable modeling. In a nutshell, the aim is to:
- propose a method for cross-lingual generalization of multi-lingual BERT using typological information;
- evaluate the proposed method on cross-lingual parsing;
- evaluate if results generalize to other tasks, for example cross-lingual named entity recognition.
[1] "Deep Contextualized Word Representations" Matthew Peters et al.
[2] "BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding" Jacob Devlin et al.
[3] "How multilingual is Multilingual BERT?" Telmo Pires et al.
[4] "Zero-resource Dependency Parsing: Boosting Delexicalized Cross-lingual Transfer with Linguistic Knowledge" Lauriane Aufrant et al.
[5] "Target Language-Aware Constrained Inference for Cross-lingual Dependency Parsing" Tao Meng et al.
🌐
https://news.1rj.ru/str/Apply_Now_Andishehsazan
Title: Cross-lingual transfer with multi-lingual BERT via linguistically informed fine-tuning
- Duration: 5-6 months, during the year 2020
- Location: LIMSI, Orsay (south of Paris)
- Supervisor: Caio Corro - http://caio-corro.fr/
- Team: Spoken Language Processing / Traitement Automatique de la Parole
- Contact: caio.corro@limsi.fr
Context
Recently, much attention has been paid to large scale pre-training of context-sensitive representations (or context-sensitive word embeddings), in particular ELMO [1] and BERT [2] models. The main idea is to pre-train the first layers of a neural network on a large amount of unlabeled data before fine-tuning the rest of the network on a downstream task. As such, context-sensitive representations allow to lower annotation cost and improve classification performance on a wide range of tasks.
The multilingual BERT model pre-trains context sensitive representations on a collection of texts in 104 languages instead of texts in a single language. One question that arises is whether we can use the multilingual BERT model for cross-lingual learning,
that is training a model on a subset of these languages (source languages) and testing it on a different subset (target languages). This problem is both important under a research perspective (how can we learn multi-lingual representations of typologically diverse languages?) and under an applied industry perspective (i.e. increase language coverage of NLP-based products at low cost). Previous work observed that cross-lingual transfert based on multi-lingual BERT works best for typological similar languages (i.e. languages with similar word order), which is expected but disappointing [3].
This internship will focus on multilingual dependency parsing with the Universal Dependency treebank https://universaldependencies.org/ . Previous work has considered re-ordering source language sentences with respect to word order in target languages [4]. However, re-ordering is not possible for unsupervised large scale pre-training where syntactic structures is not annotated. A different line of work proposed to force word order statistics at test time using constraints [5], but this method is based on a costly lagrangian optimization procedure and cannot be applied on a per sentence basis. Alternatively, we propose to explore fine-tuning methods for multi-lingual BERT model using a linguistically informed training algorithm, i.e. to use dominant word order information (is the object placed before or after the verb in a given language?) to ensure unsupervised transfer to target languages.
Missions
The successful candidate will develop neural network architectures and training algorithms for cross-lingual generalization of pre-trained context-sensitive representations. The main evaluation task will be cross-lingual dependency parsing. As there are many ways to tackle this problem, the specific approach will be determined by the intern aspiration, which could be for example posterior regularization or latent variable modeling. In a nutshell, the aim is to:
- propose a method for cross-lingual generalization of multi-lingual BERT using typological information;
- evaluate the proposed method on cross-lingual parsing;
- evaluate if results generalize to other tasks, for example cross-lingual named entity recognition.
[1] "Deep Contextualized Word Representations" Matthew Peters et al.
[2] "BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding" Jacob Devlin et al.
[3] "How multilingual is Multilingual BERT?" Telmo Pires et al.
[4] "Zero-resource Dependency Parsing: Boosting Delexicalized Cross-lingual Transfer with Linguistic Knowledge" Lauriane Aufrant et al.
[5] "Target Language-Aware Constrained Inference for Cross-lingual Dependency Parsing" Tao Meng et al.
🌐
https://news.1rj.ru/str/Apply_Now_Andishehsazan
Telegram
Apply Now
https://news.1rj.ru/str/Apply_Now_Andishehsazan
📑اعلام پوزیشنهای مستر و دکتری و پستداک با فاند
📑اعلام پوزیشنهای مستر و دکتری و پستداک با فاند
Forwarded from Apply Now
Master R2 Internship in Natural Language Processing: weakly supervised learning for hate speech detection
Motivations and context
Recent years have seen a tremendous development of Internet and social networks. Unfortunately, the dark side of this growth is an increase in hate speech. Only a small percentage of people use the Internet for unhealthy activities such as hate speech. However, the impact of this low percentage of users is extremely damaging.
Hate speech is the subject of different national and international legal frameworks. Manual monitoring and moderating the Internet and the social media content to identify and remove hate speech is extremely expensive. This internship aims at designing methods for automatic learning of hate speech detection systems on the Internet and social media data. Despite the studies already published on this subject, the results show that the task remains very difficult (Schmidt et al., 2017; Zhang et al., 2018).
More info
🌐
https://news.1rj.ru/str/Apply_Now_Andishehsazan
Motivations and context
Recent years have seen a tremendous development of Internet and social networks. Unfortunately, the dark side of this growth is an increase in hate speech. Only a small percentage of people use the Internet for unhealthy activities such as hate speech. However, the impact of this low percentage of users is extremely damaging.
Hate speech is the subject of different national and international legal frameworks. Manual monitoring and moderating the Internet and the social media content to identify and remove hate speech is extremely expensive. This internship aims at designing methods for automatic learning of hate speech detection systems on the Internet and social media data. Despite the studies already published on this subject, the results show that the task remains very difficult (Schmidt et al., 2017; Zhang et al., 2018).
More info
🌐
https://news.1rj.ru/str/Apply_Now_Andishehsazan
Telegram
Apply Now
https://news.1rj.ru/str/Apply_Now_Andishehsazan
📑اعلام پوزیشنهای مستر و دکتری و پستداک با فاند
📑اعلام پوزیشنهای مستر و دکتری و پستداک با فاند
چهارمین دوره ی جشنواره بازی های رایانه ای،فکری و محیطی – لیگا
http://ligaofficial.ir/%da%86%d9%87%d8%a7%d8%b1%d9%85%db%8c%d9%86-%d8%af%d9%88%d8%b1%d9%87-%db%8c-%d8%ac%d8%b4%d9%86%d9%88%d8%a7%d8%b1%d9%87-%d8%a8%d8%a7%d8%b2%db%8c-%d9%87%d8%a7%db%8c-%d8%b1%d8%a7%db%8c%d8%a7%d9%86%d9%87/
http://ligaofficial.ir/%da%86%d9%87%d8%a7%d8%b1%d9%85%db%8c%d9%86-%d8%af%d9%88%d8%b1%d9%87-%db%8c-%d8%ac%d8%b4%d9%86%d9%88%d8%a7%d8%b1%d9%87-%d8%a8%d8%a7%d8%b2%db%8c-%d9%87%d8%a7%db%8c-%d8%b1%d8%a7%db%8c%d8%a7%d9%86%d9%87/
Training Sessions - Shiraz.pdf
140.3 KB
Training Sessions - Shiraz.pdf
♦استخدام ارتش در استان فارس
🔹مسئول استخدام ارتش در جنوب کشور: در حال حاضر دانشگاه افسری امام علی(ع) در نیروی زمینی و مقطع دیپلم تجربی و ریاضی که معدل کل آنها بالای 14 و معدل کتبی آنان 10 باشد،اقدام به پذیرش نیرو میکند.
🔹دانشآموزانی که در پایه 12 مشغول به تحصیل هستند میتوانند برای پذیرش و استخدام در ارتش اقدام کنند.
🔹برای مقاطع بالاتر از دیپلم نیز در شهریورماه هر سال ارتش جمهوری اسلامی امکان استخدام فراهم میکند.
🔹 متقاضیان تا ۱۵ دی ماه امسال فرصت ثبت نام دارند.
🔹مسئول استخدام ارتش در جنوب کشور: در حال حاضر دانشگاه افسری امام علی(ع) در نیروی زمینی و مقطع دیپلم تجربی و ریاضی که معدل کل آنها بالای 14 و معدل کتبی آنان 10 باشد،اقدام به پذیرش نیرو میکند.
🔹دانشآموزانی که در پایه 12 مشغول به تحصیل هستند میتوانند برای پذیرش و استخدام در ارتش اقدام کنند.
🔹برای مقاطع بالاتر از دیپلم نیز در شهریورماه هر سال ارتش جمهوری اسلامی امکان استخدام فراهم میکند.
🔹 متقاضیان تا ۱۵ دی ماه امسال فرصت ثبت نام دارند.
Forwarded from Apply Now
بورسیه کارشناسی ارشد در رشته های ارائه شده دانشگاه گنت بلژیک
About the Master Mind scholarships
It is estimated that 30 international students (to be divided over the different Flemish higher education institutions) will be able to benefit from a Master Mind scholarship to start their studies in the academic year 2019-2020.
The scholarship fee consists of:
• Maximum allowance of € 8000 per academic year
• Minimum duration of one academic year ( 60 ECTS)
• Maximum for the full duration of the programme ( 2 academic years, 120 ECTS) on the condition that during the first academic year a minimum of 54 ECTS credits has been obtained
رشته های ارائه شده:
Faculty of Arts and Philosophy
Master of Arts in African Studies
Master of Arts in Global Studies
Research Master of Arts in Philosophy
Faculty of Law and Criminology
European Master of Laws in Law and Economics
Master of Laws in European Union Law
Master of Laws in International and European Law
Master of Laws in International Business Law
Master of Science in Maritime Science
Faculty of Sciences
International Master of Science in Agro- and Environmental Nematology
International Master of Science in Marine Biological Resources – main subject Applied Marine Ecology and Conservation
International Master of Science in Marine Biological Resources – main subject Global Ocean Change
International Master of Science in Marine Biological Resources – main subject Management of Living Marine Resources
International Master of Science in Marine Biological Resources – main subject Marine Environment Health
International Master of Science in Marine Biological Resources – main subject Marine Food Production
Master of Science in Biochemistry and Biotechnology
Master of Science in Bioinformatics – main subject Bioscience Engineering
Master of Science in Bioinformatics – main subject Engineering
Master of Science in Bioinformatics – main subject Systems Biology
Master of Science in Biology
Master of Science in Chemistry
Master of Science in Geology
Master of Science in Marine and Lacustrine Science and Management
Faculty of Medicine and Health Sciences
Master of Science in Biomedical Sciences
Faculty of Engineering and Architecture
European Master of Science in Nuclear Fusion and Engineering Physics
European Master of Science in Photonics
International Master of Science in Biomedical Engineering
Master of Science in Bioinformatics – main subject Engineering
Master of Science in Biomedical Engineering
Master of Science in Chemical Engineering
Master of Science in Civil Engineering
Master of Science in Computer Science Engineering
Master of Science in Electrical Engineering – main subject Communication and Information Technology
Master of Science in Electrical Engineering – main subject Electronic Circuits and Systems
Master of Science in Electromechanical Engineering – main subject Control Engineering and Automation
Master of Science in Electromechanical Engineering – main subject Electrical Power Engineering
Master of Science in Electromechanical Engineering – main subject Maritime Engineering
Master of Science in Electromechanical Engineering – main subject Mechanical Construction
Master of Science in Electromechanical Engineering – main subject Mechanical Energy Engineering
Master of Science in Engineering Physics
Master of Science in Fire Safety Engineering
Master of Science in Industrial Engineering and Operations Research
Master of Science in Sustainable Materials Engineering
Master of Science in Textile Engineering
Faculty of Economics and Business Administration
Master of Science in Business Economics – main subject Accountancy
Master of Science in Business Economics – main subject Corporate Finance
Master of Science in Business Economics – main subject Marketing
Master of Science in Business
بهترین کانال برای پیدا کردن پوزیشن سراسر جهان
💣با ما همراه باشید
https://news.1rj.ru/str/Apply_Now_Andishehsazan
About the Master Mind scholarships
It is estimated that 30 international students (to be divided over the different Flemish higher education institutions) will be able to benefit from a Master Mind scholarship to start their studies in the academic year 2019-2020.
The scholarship fee consists of:
• Maximum allowance of € 8000 per academic year
• Minimum duration of one academic year ( 60 ECTS)
• Maximum for the full duration of the programme ( 2 academic years, 120 ECTS) on the condition that during the first academic year a minimum of 54 ECTS credits has been obtained
رشته های ارائه شده:
Faculty of Arts and Philosophy
Master of Arts in African Studies
Master of Arts in Global Studies
Research Master of Arts in Philosophy
Faculty of Law and Criminology
European Master of Laws in Law and Economics
Master of Laws in European Union Law
Master of Laws in International and European Law
Master of Laws in International Business Law
Master of Science in Maritime Science
Faculty of Sciences
International Master of Science in Agro- and Environmental Nematology
International Master of Science in Marine Biological Resources – main subject Applied Marine Ecology and Conservation
International Master of Science in Marine Biological Resources – main subject Global Ocean Change
International Master of Science in Marine Biological Resources – main subject Management of Living Marine Resources
International Master of Science in Marine Biological Resources – main subject Marine Environment Health
International Master of Science in Marine Biological Resources – main subject Marine Food Production
Master of Science in Biochemistry and Biotechnology
Master of Science in Bioinformatics – main subject Bioscience Engineering
Master of Science in Bioinformatics – main subject Engineering
Master of Science in Bioinformatics – main subject Systems Biology
Master of Science in Biology
Master of Science in Chemistry
Master of Science in Geology
Master of Science in Marine and Lacustrine Science and Management
Faculty of Medicine and Health Sciences
Master of Science in Biomedical Sciences
Faculty of Engineering and Architecture
European Master of Science in Nuclear Fusion and Engineering Physics
European Master of Science in Photonics
International Master of Science in Biomedical Engineering
Master of Science in Bioinformatics – main subject Engineering
Master of Science in Biomedical Engineering
Master of Science in Chemical Engineering
Master of Science in Civil Engineering
Master of Science in Computer Science Engineering
Master of Science in Electrical Engineering – main subject Communication and Information Technology
Master of Science in Electrical Engineering – main subject Electronic Circuits and Systems
Master of Science in Electromechanical Engineering – main subject Control Engineering and Automation
Master of Science in Electromechanical Engineering – main subject Electrical Power Engineering
Master of Science in Electromechanical Engineering – main subject Maritime Engineering
Master of Science in Electromechanical Engineering – main subject Mechanical Construction
Master of Science in Electromechanical Engineering – main subject Mechanical Energy Engineering
Master of Science in Engineering Physics
Master of Science in Fire Safety Engineering
Master of Science in Industrial Engineering and Operations Research
Master of Science in Sustainable Materials Engineering
Master of Science in Textile Engineering
Faculty of Economics and Business Administration
Master of Science in Business Economics – main subject Accountancy
Master of Science in Business Economics – main subject Corporate Finance
Master of Science in Business Economics – main subject Marketing
Master of Science in Business
بهترین کانال برای پیدا کردن پوزیشن سراسر جهان
💣با ما همراه باشید
https://news.1rj.ru/str/Apply_Now_Andishehsazan
Telegram
Apply Now
https://news.1rj.ru/str/Apply_Now_Andishehsazan
📑اعلام پوزیشنهای مستر و دکتری و پستداک با فاند
📑اعلام پوزیشنهای مستر و دکتری و پستداک با فاند
China's APT20 Hacks Detected Bypassing Two-Factor in Attacks
https://gizmodo.com/chinese-hackers-bypass-2fa-in-attacks-spanning-10-count-1840613473
https://gizmodo.com/chinese-hackers-bypass-2fa-in-attacks-spanning-10-count-1840613473
Gizmodo
Chinese Hackers Bypass 2FA in Attacks Spanning 10 Countries
A Chinese hacking group believed to operate on behalf of the Beijing government has learned how to bypass two-factor authentication (2FA) in attacks on government and industry targets, ZDNet reported on Monday.