Warning
Mae'r hysbyseb swydd hon wedi dod i ben ac mae'r ceisiadau wedi cau.
Research Fellow - Efficient Machine Learning Systems
| Dyddiad hysbysebu: | 31 Mai 2024 |
|---|---|
| Cyflog: | £34,980 i £40,521 bob blwyddyn |
| Oriau: | Llawn Amser |
| Dyddiad cau: | 14 Mehefin 2024 |
| Lleoliad: | Southampton, Hampshire |
| Gweithio o bell: | Ar y safle yn unig |
| Cwmni: | University of Southampton |
| Math o swydd: | Cytundeb |
| Cyfeirnod swydd: | 2746824FP |
Crynodeb
You will join our collaborative team to work on an EPSRC-funded project led by Dr. Jagmohan Chauhan in an exciting area of embedded machine learning. The post will be based at the University of Southampton. You will be working with Dr. Jagmohan Chauhan (PI), a team of PhD students, and other collaborators such as Pete Warden (Stanford, previously Google), and OnSemi. Note that the current post is for one year. But there is a very strong chance of another year(s) extension on related projects.
As part of your roles, you will design and develop ML algorithms that make deep learning models learn on the fly and solve multiple tasks efficiently on embedded devices. You will write and submit academic papers and project deliverables, and travel to academic conferences or project meetings to present your work and represent the team.
You must have a PhD* in CS or Engineering (Electrical/Electronics), with specialization in one or more of the following fields: Machine Learning and embedded systems. An ideal candidate will possess knowledge of audio signal processing, continual learning, and have good interpersonal & communication skills.
Why us? The University of Southampton is a top university (1% of world universities) and the School of ECS is one of the top CS departments in the UK. Southampton is a vibrant city by the water, a hub for technology companies, and is very close to London.
We as a team and group have a constant presence by publishing and getting engaged, in top-tier conferences and journals in the area of Systems, ML, ubiquitous computing, and signal processing. We have a positive and vibrant environment, and, in this project, you will have an opportunity to work on cutting-edge technology while having fun. We have a large network of collaborations with academics at Imperial, KCL, Newcastle, Cambridge, Cornell, and industrial labs such as Samsung AI, and Bell Labs in case you are looking to foster further collaborations and strengthen your network. You will also have an opportunity to join the International Centre for Spatial Computational Learning and ARM-ECS Center.
We strongly encourage interested candidates to contact Dr Jagmohan Chauhan (j.chauhan@soton.ac.uk) to further discuss this role.
There is a great range of benefits that includes a contributory pension scheme; holiday entitlement of 30 days plus 8 bank holidays and 6 additional holidays (closure days); subsidized health and fitness facilities on-site; cycle to work scheme; and a range of discounts.
https://talentedu.com/ecs/
*Applications will be considered from candidates who are working towards or nearing completion of a relevant PhD qualification. The title of Research Fellow will be applied upon completion of the PhD. Prior to the qualification being awarded the title of Senior Research Assistant will be given.
We are committed to equality, diversity and inclusion and welcome applicants who support our mission of inclusivity.
Apply by 11.59 pm GMT on the closing date. For assistance contact Recruitment on +44(0)2380 592750 or recruitment@soton.ac.uk quoting the job number.
As part of your roles, you will design and develop ML algorithms that make deep learning models learn on the fly and solve multiple tasks efficiently on embedded devices. You will write and submit academic papers and project deliverables, and travel to academic conferences or project meetings to present your work and represent the team.
You must have a PhD* in CS or Engineering (Electrical/Electronics), with specialization in one or more of the following fields: Machine Learning and embedded systems. An ideal candidate will possess knowledge of audio signal processing, continual learning, and have good interpersonal & communication skills.
Why us? The University of Southampton is a top university (1% of world universities) and the School of ECS is one of the top CS departments in the UK. Southampton is a vibrant city by the water, a hub for technology companies, and is very close to London.
We as a team and group have a constant presence by publishing and getting engaged, in top-tier conferences and journals in the area of Systems, ML, ubiquitous computing, and signal processing. We have a positive and vibrant environment, and, in this project, you will have an opportunity to work on cutting-edge technology while having fun. We have a large network of collaborations with academics at Imperial, KCL, Newcastle, Cambridge, Cornell, and industrial labs such as Samsung AI, and Bell Labs in case you are looking to foster further collaborations and strengthen your network. You will also have an opportunity to join the International Centre for Spatial Computational Learning and ARM-ECS Center.
We strongly encourage interested candidates to contact Dr Jagmohan Chauhan (j.chauhan@soton.ac.uk) to further discuss this role.
There is a great range of benefits that includes a contributory pension scheme; holiday entitlement of 30 days plus 8 bank holidays and 6 additional holidays (closure days); subsidized health and fitness facilities on-site; cycle to work scheme; and a range of discounts.
https://talentedu.com/ecs/
*Applications will be considered from candidates who are working towards or nearing completion of a relevant PhD qualification. The title of Research Fellow will be applied upon completion of the PhD. Prior to the qualification being awarded the title of Senior Research Assistant will be given.
We are committed to equality, diversity and inclusion and welcome applicants who support our mission of inclusivity.
Apply by 11.59 pm GMT on the closing date. For assistance contact Recruitment on +44(0)2380 592750 or recruitment@soton.ac.uk quoting the job number.
Aelod balch o'r cynllun cyflogwyr Hyderus o ran Anabledd
Hyderus o ran Anabledd
Gwybodaeth am Hyderus o ran Anabledd
Yn gyffredinol, bydd cyflogwr Hyderus o ran Anabledd yn cynnig cyfweliad i unrhyw ymgeisydd sy'n datgan eu bod yn anabl ac yn bodloni'r meini prawf lleiaf ar gyfer y swydd fel y diffinnir gan y cyflogwr. Mae'n bwysig nodi, mewn rhai sefyllfaoedd recriwtio fel nifer fawr o ymgeiswyr, cyfnod tymhorol ac amseroedd prysur iawn, efallai y bydd y cyflogwr am gyfyngu ar y niferoedd cyffredinol o gyfweliadau a gynigir i bobl anabl a phobl nad ydynt yn anabl. Am fwy o fanylion ewch i Hyderus o ran Anabledd.