دو موقعیت دکتری کامپیوتر
فول فاند
اروپا
PhD candidate will explore how cutting-edge data analysis tools, including machine learning (ML), can be applied and tailored to answer fundamental cellular biology questions relying on such super-resolved images. This project combines timely analytical challenges with deep-rooted applications in life science.
We are looking for a PhD candidate with MS majors in either engineering/computer science/physics/mathematics. Experience with ML implementation, graphs and/or microscopy data is a plus.
More information & application
https://su.se/english/about-the-university/work-at-su/available-jobs/phd-student-positions-1.507588?rmpage=job&rmjob=19938&rmlang=UK
Deadline: 21/02/23
Contact: For more information, please contact project leader, Associate Professor, Juliette Griffie, juliette.griffie@dbb.su.se.
Keywords: spatial point patterns, graph neural network & microscopy image analysis
فول فاند
اروپا
PhD candidate will explore how cutting-edge data analysis tools, including machine learning (ML), can be applied and tailored to answer fundamental cellular biology questions relying on such super-resolved images. This project combines timely analytical challenges with deep-rooted applications in life science.
We are looking for a PhD candidate with MS majors in either engineering/computer science/physics/mathematics. Experience with ML implementation, graphs and/or microscopy data is a plus.
More information & application
https://su.se/english/about-the-university/work-at-su/available-jobs/phd-student-positions-1.507588?rmpage=job&rmjob=19938&rmlang=UK
Deadline: 21/02/23
Contact: For more information, please contact project leader, Associate Professor, Juliette Griffie, juliette.griffie@dbb.su.se.
Keywords: spatial point patterns, graph neural network & microscopy image analysis
www.su.se
PhD Student Positions - Stockholm University
موقعیت دکتری مهندسی
مالزی
PhD student at the School of Engineering, Monash University Malaysia. The topic is on applying deep learning/ machine learning in medical images (e.g., chest X-rays, mammograms, CT scans, etc.).
Benefits:
- Tuition fees waived
- MYR 2,800/ month, stipend
Requirements:
- A Master's degree or a 4-year Bachelor’s degree in Computer Science, Electrical Engineering or similar. A first class degree is required for either the Bachelor’s or Master’s (preferably both)
- Good knowledge of mathematics and algorithms.
- Good knowledge of using deep learning techniques for solving computer vision problems (e.g., detection, segmentation, and/ or classification).
- Fluency in Python
- Good knowledge with: PyTorch, TensorFlow, OpenCV (or any alternatives).
- English fluency, both written and spoken.
For more details, please contact and send your latest/ updated CV and academic transcripts to Dr. Maxine Tan at MaxineDOTTanATmonash.edu.
The scholarship is opened to both local (Malaysian) and international students
مالزی
PhD student at the School of Engineering, Monash University Malaysia. The topic is on applying deep learning/ machine learning in medical images (e.g., chest X-rays, mammograms, CT scans, etc.).
Benefits:
- Tuition fees waived
- MYR 2,800/ month, stipend
Requirements:
- A Master's degree or a 4-year Bachelor’s degree in Computer Science, Electrical Engineering or similar. A first class degree is required for either the Bachelor’s or Master’s (preferably both)
- Good knowledge of mathematics and algorithms.
- Good knowledge of using deep learning techniques for solving computer vision problems (e.g., detection, segmentation, and/ or classification).
- Fluency in Python
- Good knowledge with: PyTorch, TensorFlow, OpenCV (or any alternatives).
- English fluency, both written and spoken.
For more details, please contact and send your latest/ updated CV and academic transcripts to Dr. Maxine Tan at MaxineDOTTanATmonash.edu.
The scholarship is opened to both local (Malaysian) and international students
موقعیت دکتری/پستداک
Ph.D/postdoc opportunities at Imperial College/HEC Montreal to study inverse problems with transportation applications.
In many areas of science and engineering inverse problems arise. These problems consider a set of field observations and aim to derive the causal factors that generated the data. Inverse problems are difficult to tackle because they are underdetermined, i.e., there is often a, possibly infinite, set of causal factors that are consistent with the field data. These solutions are then used to tackle control problems. This project aims to characterize the set of solutions and to quantify their impact on the solution set of the control problems. This ultimately enables the design of robust causal inference and robust counterfactual analysis techniques.
This project develops compute-efficient optimization techniques to tackle these problems. The project can cover research areas such as bilevel optimization, fixed-point problems, game theory, traffic assignment, travel demand estimation.
The project is motivated by high-dimensional inverse problems that arise in the field of urban mobility and transportation. The inverse problems consider traffic field data that describes congestion patterns and aim to derive the travel demand that generated these congestion patterns. Control problems include congestion pricing and traffic management problems.
Research Team.
The researcher will be co-advised by Prof. Dario Paccagnan (Department of Computing, Imperial College London) and Prof. Carolina Osorio (Scale AI Research Chair, Department of Decision Sciences, HEC Montreal; Google Research). Academic affiliations can be at either Imperial College or at HEC Montreal with potential affiliations to various research centers (e.g., CIRRELT, GERAD) and numerous career opportunities within the Scale AI and the IVADO ecosystems. Details on the PhD program at Imperial College can be found at link. Similarly, for HEC Montreal, see link.
Application process.
A strong background in mathematics, operations research, optimization, game theory, control theory, computer science, statistics, or other related disciplines is required. A successful candidate should have proficiency in programming and an interest in transportation applications. Applicants are invited to submit: (i) a full CV, (ii) a copy of all their university-level transcripts, (iii) a short statement (at most 3 pages) describing why they want to work on this topic, what subtopics they would like to focus on (e.g., describe the first few papers they’d like to work on) and why they think they are qualified to do so; (iv) the names and contact details of three references (including graduate supervisors). If desired, applicants can include a copy of one of their scientific publications. All documents should be compiled into a single pdf file and send to : univ.vacancies@gmail.com with the subject “Application Inverse Problems Research".
Ph.D/postdoc opportunities at Imperial College/HEC Montreal to study inverse problems with transportation applications.
In many areas of science and engineering inverse problems arise. These problems consider a set of field observations and aim to derive the causal factors that generated the data. Inverse problems are difficult to tackle because they are underdetermined, i.e., there is often a, possibly infinite, set of causal factors that are consistent with the field data. These solutions are then used to tackle control problems. This project aims to characterize the set of solutions and to quantify their impact on the solution set of the control problems. This ultimately enables the design of robust causal inference and robust counterfactual analysis techniques.
This project develops compute-efficient optimization techniques to tackle these problems. The project can cover research areas such as bilevel optimization, fixed-point problems, game theory, traffic assignment, travel demand estimation.
The project is motivated by high-dimensional inverse problems that arise in the field of urban mobility and transportation. The inverse problems consider traffic field data that describes congestion patterns and aim to derive the travel demand that generated these congestion patterns. Control problems include congestion pricing and traffic management problems.
Research Team.
The researcher will be co-advised by Prof. Dario Paccagnan (Department of Computing, Imperial College London) and Prof. Carolina Osorio (Scale AI Research Chair, Department of Decision Sciences, HEC Montreal; Google Research). Academic affiliations can be at either Imperial College or at HEC Montreal with potential affiliations to various research centers (e.g., CIRRELT, GERAD) and numerous career opportunities within the Scale AI and the IVADO ecosystems. Details on the PhD program at Imperial College can be found at link. Similarly, for HEC Montreal, see link.
Application process.
A strong background in mathematics, operations research, optimization, game theory, control theory, computer science, statistics, or other related disciplines is required. A successful candidate should have proficiency in programming and an interest in transportation applications. Applicants are invited to submit: (i) a full CV, (ii) a copy of all their university-level transcripts, (iii) a short statement (at most 3 pages) describing why they want to work on this topic, what subtopics they would like to focus on (e.g., describe the first few papers they’d like to work on) and why they think they are qualified to do so; (iv) the names and contact details of three references (including graduate supervisors). If desired, applicants can include a copy of one of their scientific publications. All documents should be compiled into a single pdf file and send to : univ.vacancies@gmail.com with the subject “Application Inverse Problems Research".
موقعیت پستداک
دانشگاه آکسفورد
postdoc to work on logic + machine learning + constraint solving + program synthesis at the University of Oxford.
An ideal candidate will have experience in some/all the areas of program synthesis; inductive logic programming; answer set programming, sat solving, or constraint solving.
The start date and working conditions are highly flexible.
Contact me (andrew.cropper@cs.ox.ac.uk) if interested.
The full details are here:
https://www.cs.ox.ac.uk/news/2129-full.html
دانشگاه آکسفورد
postdoc to work on logic + machine learning + constraint solving + program synthesis at the University of Oxford.
An ideal candidate will have experience in some/all the areas of program synthesis; inductive logic programming; answer set programming, sat solving, or constraint solving.
The start date and working conditions are highly flexible.
Contact me (andrew.cropper@cs.ox.ac.uk) if interested.
The full details are here:
https://www.cs.ox.ac.uk/news/2129-full.html
Department of Computer Science
Research Associate on the AutoCS project
163506
موقعیت پستداک پنجساله
آلمان
PostDoc position in the recently established Center for Artificial Intelligence in Public Health Research, which is part of Robert Koch Institute, in Berlin, Germany. The position will be part of a larger third-party project that will be based in the research group "Climate and Societal Analytics".
Key competencies:
Research experience with machine learning for process modelling and data exploration
Research experience with causal inference and/or symbolic regression
Bonus:
Knowledge/Experience in either climate sciences or infectious disease modelling
All details for the position can be found here:
RKI - Careers - Scientific staff member - Climate and health research (all genders)
Deadline: March 6, 2023
Start of project: April 2023
آلمان
PostDoc position in the recently established Center for Artificial Intelligence in Public Health Research, which is part of Robert Koch Institute, in Berlin, Germany. The position will be part of a larger third-party project that will be based in the research group "Climate and Societal Analytics".
Key competencies:
Research experience with machine learning for process modelling and data exploration
Research experience with causal inference and/or symbolic regression
Bonus:
Knowledge/Experience in either climate sciences or infectious disease modelling
All details for the position can be found here:
RKI - Careers - Scientific staff member - Climate and health research (all genders)
Deadline: March 6, 2023
Start of project: April 2023
موقعیت پستداک یادگیری ماشین
لندن
PostDoc in Explainable RL & Trust @ Imperial College London (Aldo Faisal)
PostDoctoral Research Associate in Machine & Human Learning (Explainable AI & Trust in Machine Learning)
The Lab of Prof Aldo Faisal at Imperial College London (www.FaisalLab.org) based in the Dept. of Computing and the Dept. of Bioengineering at is seeking to hire a Post-Doctoral Research Associate (PDRA) to develop and lead projects in interpretable and explainable machine learning and its interface with cognitive and neurosciences - because machine learned explainability and interpretability and human trust require us to study and investigate how the human mind responds to the artificial mind.
Our has pioneered novel technologies for human-interfacing AI, and for measuring human trust in said AI. We want to understand how we can interface with human users interacting with AI systems on a cognitive level, to help them achieve the best outcome in their activities. The work applies to a wide application area, e.g. from clinical decision support systems based on reinforcement learning (Komorowski et. al, Nature Medicine 2018; Gottessmann et al., Nature Medicine, 2019), interpretable reinforcement learning algorithms for human-machine interaction (Beyret et al, IROS 2019). We have always paired this foundational technical work with worklinking AI and neuroscience for practical uses (e.g. Kadirvelu et Faisal, Nature Med, 2023; Ricotti et Faisal, Nature Med, 2023), such as our last online experiments to quantify and measure human trust in AI algorithms (Shafti et Faisal, arxiv, 2022).
https://www.imperial.ac.uk/jobs/description/ENG02471/research-associate-machine-human-learning-explainable-ai-trust-machine-learning/
لندن
PostDoc in Explainable RL & Trust @ Imperial College London (Aldo Faisal)
PostDoctoral Research Associate in Machine & Human Learning (Explainable AI & Trust in Machine Learning)
The Lab of Prof Aldo Faisal at Imperial College London (www.FaisalLab.org) based in the Dept. of Computing and the Dept. of Bioengineering at is seeking to hire a Post-Doctoral Research Associate (PDRA) to develop and lead projects in interpretable and explainable machine learning and its interface with cognitive and neurosciences - because machine learned explainability and interpretability and human trust require us to study and investigate how the human mind responds to the artificial mind.
Our has pioneered novel technologies for human-interfacing AI, and for measuring human trust in said AI. We want to understand how we can interface with human users interacting with AI systems on a cognitive level, to help them achieve the best outcome in their activities. The work applies to a wide application area, e.g. from clinical decision support systems based on reinforcement learning (Komorowski et. al, Nature Medicine 2018; Gottessmann et al., Nature Medicine, 2019), interpretable reinforcement learning algorithms for human-machine interaction (Beyret et al, IROS 2019). We have always paired this foundational technical work with worklinking AI and neuroscience for practical uses (e.g. Kadirvelu et Faisal, Nature Med, 2023; Ricotti et Faisal, Nature Med, 2023), such as our last online experiments to quantify and measure human trust in AI algorithms (Shafti et Faisal, arxiv, 2022).
https://www.imperial.ac.uk/jobs/description/ENG02471/research-associate-machine-human-learning-explainable-ai-trust-machine-learning/
Imperial College London
Jobs
Join Imperial and be part of a world leading community of research, teaching and innovation.
موقعیت پستداک
تعامل انسان و ربات
منچستر، انگلیس
Postdoc in Human-Robot Interaction, University of Manchester UK
A Postdoctoral Research Associate in Human-Robot Interaction is required for a period of 12 months (with possible extension) to work on the UKRI/EPSRC project “Trustworthy Autonomous Systems Node on Trust”. This is a collaborative project of the University of Manchester’s Cognitive Robotics Lab with Heriot-Watt University Edinburgh and Imperial College London.
The candidates will carry out research on human-robot interaction for trust. A PhD in Psychology, Computer Science, Robotics, Artificial Intelligence or allied disciplines is required. Good programming skills are important, as well as human-robot interaction experiment skills.
The research fellows will be working collaboratively as part of the Cognitive Robotics Lab at the Department of Computer Science at the University of Manchester under the supervision of Professor Angelo Cangelosi. Close collaboration with the other project partners will also be required.
Expected start date of the post is 1 April 2023.
Enquiries about the vacancy, shortlisting and interviews:
Please email Professor Angelo Cangelosi for informal enquiries: Email: angelocangelosil@manchester.ac.uk
You can apply online at the following site:
https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=24607
تعامل انسان و ربات
منچستر، انگلیس
Postdoc in Human-Robot Interaction, University of Manchester UK
A Postdoctoral Research Associate in Human-Robot Interaction is required for a period of 12 months (with possible extension) to work on the UKRI/EPSRC project “Trustworthy Autonomous Systems Node on Trust”. This is a collaborative project of the University of Manchester’s Cognitive Robotics Lab with Heriot-Watt University Edinburgh and Imperial College London.
The candidates will carry out research on human-robot interaction for trust. A PhD in Psychology, Computer Science, Robotics, Artificial Intelligence or allied disciplines is required. Good programming skills are important, as well as human-robot interaction experiment skills.
The research fellows will be working collaboratively as part of the Cognitive Robotics Lab at the Department of Computer Science at the University of Manchester under the supervision of Professor Angelo Cangelosi. Close collaboration with the other project partners will also be required.
Expected start date of the post is 1 April 2023.
Enquiries about the vacancy, shortlisting and interviews:
Please email Professor Angelo Cangelosi for informal enquiries: Email: angelocangelosil@manchester.ac.uk
You can apply online at the following site:
https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=24607
www.jobs.manchester.ac.uk
Research Associate in Human-Robot Interaction:Oxford Road
موقعیت دکتری رباتیک
اروپا
Do you have a master's degree in Machine Learning, Robotics, Control, or similar and looking for a work opportunity involving academic research and real work applications?
If yes, this Ph.D. position may be the one you are looking for!
Link: https://www.tudelft.nl/over-tu-delft/werken-bij-tu-delft/vacatures/details/?nPostingId=3871&nPostingTargetId=10823&id=QEZFK026203F3VBQBLO6G68W9&LG=UK&mask=external
Deadline: February 24, 2023
You can find more info at the end of the email.
----------------
This is a four-year position, and salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities (salary indication: € 2.541,00 - € 3.247,00, 30% reduction of the taxes may apply).
Supervision team
• Cosimo's website: https://cosimodellasantina.eu/
• Jens's website: http://www.jenskober.de/
• Robert's website: http://www.robertbabuska.com/
Company involved
• Octiva: https://www.privakompano.com/
----------------
About TU Delft, 3me, and CoR:
Delft University of Technology (TUD) is the oldest and largest technical university in the Netherlands, with over 23,000 students and 3,300 scientific staff. Its high-quality teaching standards and experimental facilities are renowned, placing it among the 6th top universities in Europe and 15th in the world in the Engineering and Technology fields, and 2nd top universities in Europe and 5th in the world in the Mechanical, Aeronautical, and Manufacturing Engineer (QS Ranking 2020). It is a member of the IDEA League, a strategic alliance of five of Europe's leading technology universities.
TU Delft comprises eight faculties: among these is the 3mE Faculty (Mechanical, Maritime, and Materials Engineering), which hosts the Cognitive Robotics (CoR) department. In 2012, TU established the Delft Robotics Institute, in which CoR takes part. The Institute unites all the university's research in the field of robotics, bringing together more than 150 scientific staff from six TU Delft faculties. The aim is to get robots and humans to work together effectively in unstructured and real-world environments. Both the 'hard' robotics disciplines (mechatronics, embedded systems, control, and AI) and the 'soft' ones (human-machine interaction, user interaction, architecture, ethics, and design) are represented. A part of the Institute is the TU Delft Digital Innovation Hub called RoboValley (https://robovalley.com) established to foster collaboration with companies and technology transfer
اروپا
Do you have a master's degree in Machine Learning, Robotics, Control, or similar and looking for a work opportunity involving academic research and real work applications?
If yes, this Ph.D. position may be the one you are looking for!
Link: https://www.tudelft.nl/over-tu-delft/werken-bij-tu-delft/vacatures/details/?nPostingId=3871&nPostingTargetId=10823&id=QEZFK026203F3VBQBLO6G68W9&LG=UK&mask=external
Deadline: February 24, 2023
You can find more info at the end of the email.
----------------
This is a four-year position, and salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities (salary indication: € 2.541,00 - € 3.247,00, 30% reduction of the taxes may apply).
Supervision team
• Cosimo's website: https://cosimodellasantina.eu/
• Jens's website: http://www.jenskober.de/
• Robert's website: http://www.robertbabuska.com/
Company involved
• Octiva: https://www.privakompano.com/
----------------
About TU Delft, 3me, and CoR:
Delft University of Technology (TUD) is the oldest and largest technical university in the Netherlands, with over 23,000 students and 3,300 scientific staff. Its high-quality teaching standards and experimental facilities are renowned, placing it among the 6th top universities in Europe and 15th in the world in the Engineering and Technology fields, and 2nd top universities in Europe and 5th in the world in the Mechanical, Aeronautical, and Manufacturing Engineer (QS Ranking 2020). It is a member of the IDEA League, a strategic alliance of five of Europe's leading technology universities.
TU Delft comprises eight faculties: among these is the 3mE Faculty (Mechanical, Maritime, and Materials Engineering), which hosts the Cognitive Robotics (CoR) department. In 2012, TU established the Delft Robotics Institute, in which CoR takes part. The Institute unites all the university's research in the field of robotics, bringing together more than 150 scientific staff from six TU Delft faculties. The aim is to get robots and humans to work together effectively in unstructured and real-world environments. Both the 'hard' robotics disciplines (mechatronics, embedded systems, control, and AI) and the 'soft' ones (human-machine interaction, user interaction, architecture, ethics, and design) are represented. A part of the Institute is the TU Delft Digital Innovation Hub called RoboValley (https://robovalley.com) established to foster collaboration with companies and technology transfer
TU Delft
Job details
موقعیت دکتری کامپیوتر و آمار
اروپا
حقوق ماهیانه حدود ۴۰۰۰ یورو
مهلت اپلای: ده روز دیگر (28 فوریه
Location: Trinity College Dublin
Funding for: EU and non-EU students
Funding amount: very competitive (see Salary below)
Hours: Full Time
Closing date: 28/Feb/2023
PhD starting time: 1/Sep/2023
Project details: The School of Computer Science and Statistics in Trinity College Dublin is now inviting applications for a fully funded PhD scholarship, in the broad area of functional data and image data machine learning. The candidate will be supervised by Prof. Mimi Zhang (primary) and Prof. Michael Monaghan (secondary). The scholarship is funded by H2020/Marie-Skłodowska-Curie Joint Doctoral Network (https://flimagin3d.com/). Your PhD research will be focusing on both methodology (50% time commitment) and application (50% time commitment). For methodology, you will be working on the frontier of functional data cluster analysis. For application, you will see on the project website (PhD project #1, the machine learning pipeline) that we will develop novel machine learning algorithms to classify cell behaviour and phenotype based on FLIM data. After the PhD study, you will develop strong skills in methodology, optimization, and programming and have hands-on experience on dealing with large and complex data.
Salary: The salary consists of a monthly living allowance (€4063), mobility allowance (€600), family allowance if applicable (€495), and financial support towards the student’s conference and training travel.
Information about salary for PhDs can be read on the MSCA Horizon Europe programme call (https://ec.europa.eu/info/funding-tenders/opportunities/docs/2021-2027/horizon/wp-call/2021-2022/wp-2-msca-actions_horizon-2021-2022_en.pdf), beginning on page 78.
The salary above is funded by European Commission and is guaranteed for three years. The PhD study is funded for four years, with the fourth year funded by SFI (with stipend currently at the rate of €18,500 per annum).
Candidate description: A Bachelor’s degree in statistics, math, computer science, or closely related subjects is required. The candidate is expected to have a sound theoretical and practical knowledge on statistics, as well as strengths in programming.
How to apply: Candidates must submit their applications through the project website (www.flIMAGIN3D.com) until February 28th, 2023.
اروپا
حقوق ماهیانه حدود ۴۰۰۰ یورو
مهلت اپلای: ده روز دیگر (28 فوریه
Location: Trinity College Dublin
Funding for: EU and non-EU students
Funding amount: very competitive (see Salary below)
Hours: Full Time
Closing date: 28/Feb/2023
PhD starting time: 1/Sep/2023
Project details: The School of Computer Science and Statistics in Trinity College Dublin is now inviting applications for a fully funded PhD scholarship, in the broad area of functional data and image data machine learning. The candidate will be supervised by Prof. Mimi Zhang (primary) and Prof. Michael Monaghan (secondary). The scholarship is funded by H2020/Marie-Skłodowska-Curie Joint Doctoral Network (https://flimagin3d.com/). Your PhD research will be focusing on both methodology (50% time commitment) and application (50% time commitment). For methodology, you will be working on the frontier of functional data cluster analysis. For application, you will see on the project website (PhD project #1, the machine learning pipeline) that we will develop novel machine learning algorithms to classify cell behaviour and phenotype based on FLIM data. After the PhD study, you will develop strong skills in methodology, optimization, and programming and have hands-on experience on dealing with large and complex data.
Salary: The salary consists of a monthly living allowance (€4063), mobility allowance (€600), family allowance if applicable (€495), and financial support towards the student’s conference and training travel.
Information about salary for PhDs can be read on the MSCA Horizon Europe programme call (https://ec.europa.eu/info/funding-tenders/opportunities/docs/2021-2027/horizon/wp-call/2021-2022/wp-2-msca-actions_horizon-2021-2022_en.pdf), beginning on page 78.
The salary above is funded by European Commission and is guaranteed for three years. The PhD study is funded for four years, with the fourth year funded by SFI (with stipend currently at the rate of €18,500 per annum).
Candidate description: A Bachelor’s degree in statistics, math, computer science, or closely related subjects is required. The candidate is expected to have a sound theoretical and practical knowledge on statistics, as well as strengths in programming.
How to apply: Candidates must submit their applications through the project website (www.flIMAGIN3D.com) until February 28th, 2023.
چند موقعیت تحقیقاتی کامپیوتر
لندن
research associates on foundational AI research and security/privacy! If you are passionate about any of the above topics, consider applying. Interviews take place on a rolling basis.
Feel free to reach out with any questions (aicd@turing.ac.uk) and share with qualified candidates (e.g., PhDs close to graduation)!
Information & application:
Research Assistant: bit.ly/aicd-careers-ra
Postdoc positions. : bit.ly/aicd-careers-pdra
(Deadline 21 February)
Details
These roles will sit within the AI for Cyber Defence (AICD) Research Centre. The centre is focussed on delivering the science needed for developing autonomous and resilient cyber defence using reinforcement learning (RL) and other autonomous approaches to learning from interaction. This involves both the application of existing AI algorithms and techniques as well as fundamentally advancing AI where necessary. The technical scope of this role includes:
• Relevant foundational research on AI including making improvements to existing techniques and proposing alternatives that advance the state of the art.
• Research on open security and privacy problems that might be solved with modern ML techniques.
• Publishing in high quality peer-reviewed venues (e.g., ICML, NeurIPS, USENIX, ACM CCS, IEEE S&P).
About the Alan Turing Institute
The Alan Turing Institute is the UK’s national institute for data science and artificial intelligence. Its mission is to make great leaps in data science and artificial intelligence research in order to change the world for the better. The institute is located in the British Library in the heart of London.
لندن
research associates on foundational AI research and security/privacy! If you are passionate about any of the above topics, consider applying. Interviews take place on a rolling basis.
Feel free to reach out with any questions (aicd@turing.ac.uk) and share with qualified candidates (e.g., PhDs close to graduation)!
Information & application:
Research Assistant: bit.ly/aicd-careers-ra
Postdoc positions. : bit.ly/aicd-careers-pdra
(Deadline 21 February)
Details
These roles will sit within the AI for Cyber Defence (AICD) Research Centre. The centre is focussed on delivering the science needed for developing autonomous and resilient cyber defence using reinforcement learning (RL) and other autonomous approaches to learning from interaction. This involves both the application of existing AI algorithms and techniques as well as fundamentally advancing AI where necessary. The technical scope of this role includes:
• Relevant foundational research on AI including making improvements to existing techniques and proposing alternatives that advance the state of the art.
• Research on open security and privacy problems that might be solved with modern ML techniques.
• Publishing in high quality peer-reviewed venues (e.g., ICML, NeurIPS, USENIX, ACM CCS, IEEE S&P).
About the Alan Turing Institute
The Alan Turing Institute is the UK’s national institute for data science and artificial intelligence. Its mission is to make great leaps in data science and artificial intelligence research in order to change the world for the better. The institute is located in the British Library in the heart of London.
cezanneondemand.intervieweb.it
Research Assistant - Security, Privacy and Machine Learning
The Defence & Security programme at the Turing is looking to expand a newly formed team of researchers working on real-world security and privacy
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استارت آپ Replit اولین چت ربات "زنده" جهان را با هوش مصنوعی برای نوشتن کد راه اندازی کرد.
Ghostwriter Chat
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کند
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https://replit.com/site/ghostwriter#chatProduct
Ghostwriter Chat
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کند
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درد و سختی در کوتاه مدت
عشق و حال در بلند مدت
تجربه زندگی حداقل در اینجایی که ما زندگی میکنیم این رو به من یاد داده که نقد رو بچسب و نسیه رو ول کن . یعنی اینکه شما اینقدر پدرتون در بیاد کار کنید و پول در بیارید و خونه بخرید (در بهترین حال اگه بتونید) بعد بشه ۴۰ سالتون و دیگه حال و حوصله این رو نداشته باشید که عشق و حال کنید؟ کنار نوه و نتیجه هاتون از زندگی لذت ببرید؟ یا اینکه فکر کنید چقدر عشق و حال نکردید.
درد و سختی در کوتاه مدت
عشق و حال در بلند مدت
تجربه زندگی حداقل در اینجایی که ما زندگی میکنیم این رو به من یاد داده که نقد رو بچسب و نسیه رو ول کن . یعنی اینکه شما اینقدر پدرتون در بیاد کار کنید و پول در بیارید و خونه بخرید (در بهترین حال اگه بتونید) بعد بشه ۴۰ سالتون و دیگه حال و حوصله این رو نداشته باشید که عشق و حال کنید؟ کنار نوه و نتیجه هاتون از زندگی لذت ببرید؟ یا اینکه فکر کنید چقدر عشق و حال نکردید.
این هفته یک رویداد استارتاپ ویکند داره برگزار میشه به میزبانی ایرانمال و ثبتنام داخلش رایگانه. منتورهای خوبی هم داره. اگه فرصت دارید از سهشنبه تا جمعه صبح تا شب تو این رویداد شرکت کنید زودتر ثبتنام کنید تا ظرفیتش تکمیل نشده:
http://evand.com/events/imcevent
استارتاپویکند رویدادیه که آدمها توش ایدههای استارتاپیشون رو ارائه کوتاه میکنن، بین ۵۰-۶۰ نفر شرکت کننده مثلا ۱۰ تا ایده رو با رأیگیری انتخاب میکنن، همونجا بین خودشون تیم تشکیل میدن و شروع میکنن به ساختن یه نسخه mvp از استارتاپ. سه چهار تا ورکشاپ آموزشی داره و همزمان تیم روی ایده زیر نظر منتورها کار میکنه. در نهایت جمعه عصر محصول اولیه رو جلوی داورها تو اختتامیه پرزنت میکنن.
رویداد بسیار آموزنده و خوبیه. خصوصا اگه میخواین الفبای راهاندازی استارتاپ رو به همراه کلی سافت اسکیل دیگه در عمل یاد بگیرید.
http://evand.com/events/imcevent
استارتاپویکند رویدادیه که آدمها توش ایدههای استارتاپیشون رو ارائه کوتاه میکنن، بین ۵۰-۶۰ نفر شرکت کننده مثلا ۱۰ تا ایده رو با رأیگیری انتخاب میکنن، همونجا بین خودشون تیم تشکیل میدن و شروع میکنن به ساختن یه نسخه mvp از استارتاپ. سه چهار تا ورکشاپ آموزشی داره و همزمان تیم روی ایده زیر نظر منتورها کار میکنه. در نهایت جمعه عصر محصول اولیه رو جلوی داورها تو اختتامیه پرزنت میکنن.
رویداد بسیار آموزنده و خوبیه. خصوصا اگه میخواین الفبای راهاندازی استارتاپ رو به همراه کلی سافت اسکیل دیگه در عمل یاد بگیرید.
ایوند
رویداد استارتاپی کنگره موبایل ایران - سهشنبه ۲ اسفند ۰۱
خرید بلیت و ثبتنام رویداد استارتاپی کنگره موبایل ایران در ایوند - موضوع: استارتاپی
موقعیت دکتری کامپیوتر
فرانسه
PhD position on tensor-based unsupervised learning methods for neuroimaging data fusion.
Location: Primarily the CRAN laboratory (University of Lorraine) at Nancy, France, with visits to the MLSP laboratory (UMBC) in Maryland, USA.
The candidate will work with Prof. David Brie and Dr. Ricardo Borsoi in the CRAN laboratory, Université de Lorraine, Nancy, and with Prof. Tülay Adali at the MLSP laboratory, UMBC, USA.
Starting date: October 2023
Description: Given the recent explosion in the amount of data from multiple modalities, a fundamental problem is fusing heterogeneous datasets containing dataset-specific information. The objective of the project is to develop flexible and directly interpretable unsupervised learning algorithms based on tensor decompositions for neuroimaging data fusion. Specific objectives include the study of their theoretical properties and demonstrate their performance on multi-subject and multimodality neuroimaging data for personalized medicine applications.
Candidate profile: Master’s degree or equivalent, with experience in signal processing, machine learning or applied mathematics.
To apply: If interested, please send your application including an academic CV and a motivation letter to david.brie@univ-lorraine.fr, ricardo.borsoi@univ-lorraine.fr, and adali@umbc.edu.
For further information, see: http://ricardoborsoi.github.io/Positions/P_these_tensCRAN_UMBC_2023.pdf
فرانسه
PhD position on tensor-based unsupervised learning methods for neuroimaging data fusion.
Location: Primarily the CRAN laboratory (University of Lorraine) at Nancy, France, with visits to the MLSP laboratory (UMBC) in Maryland, USA.
The candidate will work with Prof. David Brie and Dr. Ricardo Borsoi in the CRAN laboratory, Université de Lorraine, Nancy, and with Prof. Tülay Adali at the MLSP laboratory, UMBC, USA.
Starting date: October 2023
Description: Given the recent explosion in the amount of data from multiple modalities, a fundamental problem is fusing heterogeneous datasets containing dataset-specific information. The objective of the project is to develop flexible and directly interpretable unsupervised learning algorithms based on tensor decompositions for neuroimaging data fusion. Specific objectives include the study of their theoretical properties and demonstrate their performance on multi-subject and multimodality neuroimaging data for personalized medicine applications.
Candidate profile: Master’s degree or equivalent, with experience in signal processing, machine learning or applied mathematics.
To apply: If interested, please send your application including an academic CV and a motivation letter to david.brie@univ-lorraine.fr, ricardo.borsoi@univ-lorraine.fr, and adali@umbc.edu.
For further information, see: http://ricardoborsoi.github.io/Positions/P_these_tensCRAN_UMBC_2023.pdf