项目介绍
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The research group of Björn Forsberg will recruit 1-2 PhD students in machine learning and computer vision methods to improve methods structural bioinformatics of 3D molecular representations.
Your work assignments
In this position, you will use machine learning methods and tailored feature engineering to design new methods that aim to understand the complexity of molecular life in 3D. Specifically, you will extend existing methods to quantify variation in ensembles and averages of molecular structures like proteins and incorporate established methods from computer vision to unsolved problems where they have not been deployed previously. You will have the opportunity to learn and develop high-performance computing solutions using national super-computing infrastructure and apply these methods at scale to investigate new biology. There are also opportunities for national and international collaboration in both software development and applied biological research, and integration of e.g. AlphaFold.
As a PhD student, you devote most of your time to doctoral studies and the research projects of which you are part. Your work may also include teaching or other departmental duties, up to a maximum of 20% of full-time.
Your qualifications
You have graduated (or completed courses with at least 240 credits) at master’s level, either in a computational or mathematical field of study, or with demonstrated experience in structural biology or bioinformatics.
You will be expected to independently write and evaluate software in python and C++, using git for versioning, collaborative development, testing and deployment. Evidence of experience (e.g. through GitHub user contributions) is beneficial to your application. You are expected to be resourceful and independent, but also transparent and open to both provide and receive feedback. You are expected to look for opportunities to develop your own skills and interests, and encouraged to participate in international conferences, workshops, and collaborations. Excellent oral and written communication skills in English is essential.
It is beneficial to your application to demonstrate skills or experience with data-visualization approaches (e.g. clustering, classification, deep learning, …), software development (in particularly using pytorch, C++, CUDA, or other HPC-oriented solutions), use of large-scale data, and experience in a UNIX environment. Knowledge of macromolecular structure analysis such as cryo-EM, crystallography, molecular dynamics, or similar is beneficial but not necessary.
Please motivate why you are interested in the role in your application.
Your workplace
Structural bioinformatics considers molecular structure through data, encompassing the machine-learning prediction tools like AlphaFold, the information in large-scale databases of DNA sequences and genetic evolution, as well as mining of microscopy data through image analysis. The research team led by Björn Forsberg at Linköping University focuses their efforts on electron microscopy (cryo-EM and cryo-ET) data, which reconstructs 3D models of molecular life. This subject area means we use a variety of statistical, data science & machine learning approaches. We work with collaborators all over the world to apply our methods to innovative research projects and experimental data and believe in developing generally applicable open tools and packages that can be taken up by the wider scientific community.
The team is based in the bioinformatics division within the department of Physics, Chemistry and Biology (IFM) at Linköping University, and has the backing of the data-driven life science (DDLS) program through Science for Life Laboratory (SciLifeLab). This s a 12-year initiative funded with a total of 3,7 billion SEK (~€350M) from the Knut and Alice Wallenberg Foundation to recruit and train the next-generation of data-driven life scientists and to create globally leading computational and data science capabilities in life science in Sweden. The program is a hub for cross-disciplinary life sciences, interdisciplinary work and engagement with industry, healthcare, and other national and international partners. The team also supports and leverages the national facility for cryo-EM microscopy at SciLifeLab Solna and Umeå and utilizes the most modern super-computing infrastructure in Sweden (Berzelius@NSC). Close collaborations exist within the department for macromolecular variability analysis and prediction methods for protein structures and ensembles, and with the strong environments for statistics, machine learning and computer vision at Linköping university. Collaborations also extend to e.g. the Chan-Zuckerberg Imaging Institute in San Francisco and the University of Oxford.
The employment
When taking up the post, you will be admitted to the program for doctoral studies. More information about the doctoral studies at each faculty is available at Doctoral studies at Linköping University
The employment has a duration of four years’ full-time equivalent. You will initially be employed for a period of one year. The employment will subsequently be renewed for periods of maximum duration two years, depending on your progress through the study plan. The employment may be extended up to a maximum of five years, based on the amount of teaching and departmental duties you have carried out. Further extensions can be granted in special circumstances.
Starting date by agreement, as soon as possible.
Salary and employment benefits
The salary of PhD students is determined according to a locally negotiated salary progression.
More information about employment benefits at Linköping University is available here.
Union representatives
Information about union representatives, see Help for applicants.
Application procedure
Apply for the position by clicking the “Apply” button below. Your application must reach Linköping University no later than the 20th of December 2024.
Applications and documents received after the date above will not be considered.
We welcome applicants with different backgrounds, experiences and perspectives – diversity enriches our work and helps us grow. Preserving everybody’s equal value, rights and opportunities is a natural part of who we are. Read more about our work with: Equal opportunities.
We look forward to receiving your application!
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Contact persons
Björn Forsberg
Assistant Professor
URL to this page
https://web103.reachmee.com/ext/I011/853/main?site=7&validator=d7a66c13be778ef950c393a904293789&lang=UK&rmpage=job&rmjob=25754&rmlang=UK
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