[visionlist] PhD student at KTH in machine learning and tomosynthesis
rodmore at kth.se
Thu Sep 8 07:31:40 -04 2022
PhD student position on machine learning and 3D mammography (tomosynthesis)
Tomosynthesis is a promising 3D modality for diagnosing breast cancer. Deep learning is the most successful form of artificial intelligence (AI). The aim of this project is to utilize a unique database of tomosynthesis and mammography images and new methods in deep learning to create novel diagnostic tools for breast cancer. The position offers good opportunities to gain deeper knowledge of recent techniques in deep learning such as generative adversarial networks (GAN), spherical convolutional neural networks or normal appearance autoencoders, a method developed in our group, in addition to explainable-AI and uncertainty quantification methods. The selected candidate will be part of the EU-funded European Training Network consortium BosomShield. That includes access to educational and career development activities from the network and several secondment visits to the partners.
What we offer
* The possibility to study in a dynamic and international research environment in collaboration with industries and prominent universities from all over the world.Read more<https://www.kth.se/en/studies/phd/why-1.521017>
* A workplace with many employee benefits <https://www.kth.se/en/om/work-at-kth/en-arbetsplats-med-manga-formaner-1.467932> and monthly salary according to KTH’s Doctoral student salary agreement.<https://intra.kth.se/en/anstallning/anstallningsvillkor/lon/doktorandstegen-1.572915>
* A postgraduate education at an institution that is active and supportive in matters pertaining to working conditions, gender equality and diversity as well as study environment.
* Work and study in Stockholm, close to nature and the water.
* Help to relocate and be settled in Sweden and at KTH<https://www.kth.se/en/om/work-at-kth/relocation>.
To be admitted to postgraduate education (Chapter 7, 39 § Swedish Higher Education Ordinance), the applicant must have basic eligibility in accordance with either of the following:
* passed a second cycle degree (for example a master's degree), or
* completed course requirements of at least 240 higher education credits, of which at least 60 second-cycle higher education credits, or
* acquired, in some other way within or outside the country, substantially equivalent knowledge
* lived at most 12 months in the last 3 years in Sweden
In addition to the above, there is also a mandatory requirement for English equivalent to English B/6, read more here<https://www.kth.se/en/studies/phd/admission-requirements-1.520175>
Apply for the position and admission through KTH's recruitment system.
Doctoral student focusing on machine learning and 3D mammography<https://www.kth.se/en/om/work-at-kth/lediga-jobb/what:job/jobID:519197/where:4/>
At KTH you will have the opportunity of bringing life to your ideas and, at the same time, contributing to tomorrow's society. Whatever position you have, you can take a lot of personal responsibility in a workplace that has a strong sense of fellowship.
Deadline: 29.Sep.2022 11:59 PM CEST
It is the applicant’s responsibility to ensure that the application is complete in accordance with the instructions in the advertisement.
Applications must be received at the last closing date at midnight, CET/CEST (Central European Time/entral European Summer Time).
Applications must include the following elements:
* CV including your relevant professional experience and knowledge.
* Application letter with a brief description of why you want to pursue research studies, about what your academic interests are and how they relate to your previous studies and future goals. (Maximum 2 pages long)
* Copies of diplomas and grades from previous university studies and certificates of fulfilled language requirements (see above)<https://www.kth.se/en/studies/phd/admission-requirements-1.520175>. Translations into English or Swedish if the original document is not issued in one of these languages.Copies of originals must be certified<https://www.kth.se/en/student/framtid/examen/verifiering/vidimering-av-handlingar-1.55190>.
* Representative publications or technical reports. For longer documents, please provide a summary (abstract) and a web link to the full text.
Associate Professor, PhD, Docent
KTH Royal Institute of Technology
Department of Biomedical Engineering and Health Systems
SE-141 57 Huddinge, Stockholm, Sweden
Phone: +46 8790 9787
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