From jonas.paulsen at ibv.uio.no Thu Dec 2 11:14:59 2021 From: jonas.paulsen at ibv.uio.no (Jonas Paulsen) Date: Thu, 2 Dec 2021 10:14:59 +0000 Subject: [SocBiN] Postdoc position (3 years) in Bioinformatics and 3D genome modeling at University of Oslo Message-ID: A 3-year Postdoc position in bioinformatics and 3D genome modeling is available at Department of Biosciences, University of Oslo, Norway. The focus of the group is to understand how the 3D organization of DNA inside the cell nucleus relates to critical functions in the eukaryotic cell, such as gene expression regulation and the cell cycle. See our recent publications in Nature Protoc. 2018, Nature Genetics 2019, Curr. Opin. Genet. Dev 2021 (listed below). Relevant skills: Bioinformatics, biophysics, modeling, scripting/programming Salary offered: NOK 534,400 – 615,800 per year (~ 52,000 - 60,000 EUR) Starting date: Preferably in 2022 Application deadline: 31.12.2021 Read more and apply here: https://www.jobbnorge.no/en/available-jobs/job/216462/postdoctoral-research-fellow-in-bioinformatics-and-3d-genome-modeling Recent references: [1] Paulsen, J. et al. (2019). Long-range interactions between topologically associating domains shape the four-dimensional genome during differentiation. Nature genetics, 51(5), 835-843. [2] Di Stefano, M., Paulsen, J., Jost, D., & Marti-Renom, M. A. (2021). 4D nucleome modeling. Current Opinion in Genetics & Development, 67, 25-32. [3] Paulsen, J., Ali, T. M. L., & Collas, P. (2018). Computational 3D genome modeling using Chrom3D. Nature protocols, 13(5), 1137-1152. ________________________________ Jonas Paulsen, PhD Associate Professor Section for Genetics and Evolutionary Biology (EVOGENE) Department of Biosciences University of Oslo Tel: +47 41147241 ________________________________ -------------- next part -------------- An HTML attachment was scrubbed... URL: From erik.kristiansson at chalmers.se Wed Dec 1 13:42:34 2021 From: erik.kristiansson at chalmers.se (Erik Kristiansson) Date: Wed, 1 Dec 2021 12:42:34 +0000 Subject: [SocBiN] Post-doc position in bioinformatics at Chalmers University of Technology Message-ID: <166fbe4297b646d2a1b033cb3100bda7@chalmers.se> Everyone, We have an open post-doc position in bioinformatics focused on metagenomics with applications to infection diseases and antibiotic resistant bacteria. For more information see https://www.chalmers.se/en/about-chalmers/Working-at-Chalmers/Vacancies/Pages/default.aspx?rmpage=job&rmjob=9969&rmlang=UK Best, Erik Kristiansson -- -------------------------------------------------------------------------------- Erik Kristiansson, Professor in biostatistics and bioinformatics Applied Mathematics and Statistics Department of Mathematical Sciences Chalmers University of Technology/University of Gothenburg, Sweden Email: erik.kristiansson at chalmers.se, Phone: +46 (0)31 772 3521 -------------------------------------------------------------------------------- From anders.andersson at scilifelab.se Mon Dec 6 16:36:08 2021 From: anders.andersson at scilifelab.se (Anders Andersson) Date: Mon, 6 Dec 2021 16:36:08 +0100 Subject: [SocBiN] =?utf-8?q?Postdoctoral_position_in_microbial_ecology_and?= =?utf-8?q?_bioinformatics_at_Ume=C3=A5_University?= Message-ID: Please see: https://www.umu.se/en/work-with-us/open-positions/post-doctoral-position-2-years-focused-on-phytoplankton-adaptation-to-seawater-browning_448837/ Anders Anderson -- Associate Professor SciLifeLab KTH Royal Institute of Technology Stockholm, Sweden Webpage: http://envgen.github.io/ Email: anders.andersson at scilifelab.se Phone: +46-8-5248-1414; +46-73-9838962 -------------- next part -------------- An HTML attachment was scrubbed... URL: From arne at bioinfo.se Tue Dec 7 16:49:25 2021 From: arne at bioinfo.se (Arne Elofsson) Date: Tue, 7 Dec 2021 16:49:25 +0100 Subject: [SocBiN] PhD in structural and functional protein bioinformatics Message-ID: Department of Experimental Medical Science https://lu.varbi.com/en/what:job/jobID:456054 Lund University was founded in 1666 and is repeatedly ranked among the world’s top 100 universities. The University has around 44 000 students and more than 8 000 staff based in Lund, Helsingborg and Malmö. We are united in our efforts to understand, explain and improve our world and the human condition. Lund University welcomes applicants with diverse backgrounds and experiences. We regard gender equality and diversity as a strength and an asset. *Background* In the Atkinson lab we are interested in making exciting discoveries about the evolution of protein function and structure. We work mainly with bioinformatic methods, developing our own tools and taking advantage of the wealth of available genome and predicted proteome sequences. The Atkinson lab is based in the Department of Experimental Medical Sciences in the Biomedical Centre (BMC) in Lund. You can read more about our group on our lab website here: https://atkinson-lab.com/, and about the department here: https://www.medicine.lu.se/faculty-medicine-lund-university/departments/department-experimental-medical-science One of our main research directions concerns toxin-antitoxin (TA) systems of bacteria and bacteriophages, which has led to papers in PNAS(1) and Molecular Cell(2) on toxSAS enzymes that dramatically inhibit bacterial growth though producing poisonous nucleotides, or modifying tRNA, as well as a more recent preprint on the hyper promiscuous antitoxin domain that we have named Panacea(3). Our work on toxin-antitoxins, and their evolution, structure, function and biotechnological applications was recently supported by a generous grant from the Knut and Alice Wallenberg foundation (see https://kaw.wallenberg.org/en/research/bacterias-emergency-stop-buttons). As a mechanism of defence against bacteriophages, TAs have significance for developing new biotechnological tools, as well as understanding and eventually overcoming natural barriers to phage therapy for treating antibiotic resistant infections. References 1. Jimmy, S.* et al.* *Proc Natl Acad Sci U S A* *117*, 10500-10510, (2020). 2. Kurata, T.* et al.* *Mol Cell* *81*, 3160-3170 e3169, (2021). 3. Kurata, T.*et al.* *Proc Natl Acad Sci U S A (in press) and **bioRxiv*, https://www.biorxiv.org/content/10.1101/2021.1105.1107.442387v442381, (2021). In our group, we strive for a supportive, respectful and stimulating working environment that promotes personal and professional development for all members. We are looking for a PhD student to continue the lab’s high impact work, driving new directions in toxin-antitoxin system research. A significant part of the project will be the use of deep learning methods for structural prediction such as AlphaFold2. The employment is for 4 years at full time and the start date is by agreement. *Responsibilities* In this PhD project you will be using and developing computational tools to predict the structure and biological function of toxin-antitoxin systems of bacteria and bacteriophages. Bioinformatic predictions that come out of this project will be verified experimentally through our collaborative network. Much of the project will focus on toxin-antitoxin systems, but you will also have opportunities to broaden your horizons to other molecular systems. You will have the opportunity to attend and present your work at international meetings. *Qualifications* Required qualifications: - Coding skills (preferably in Python) - Experience in structural bioinformatics - Proficiency in spoken and written English - Background understanding of, and interest in molecular biology and evolution of microbes Desirable qualifications: - Experience in creating pipelines for use with high performance computing clusters - Competence in large dataset handling - Previous use of machine learning or artificial intelligence methods, especially for structural prediction such as AlphaFold2 or RosettaFold *Eligibility* Students with basic eligibility for third-cycle studies are those who- have completed a second-cycle degree- have completed courses of at least 240 credits, of which at least 60 credits are from second-cycle courses, or- have acquired largely equivalent knowledge in some other way, in Sweden or abroad. The employment of doctoral students is regulated in the Swedish Code of Statues 1998: 80. Only those who are or have been admitted to PhD-studies may be appointed to doctoral studentships. When an appointment to a doctoral studentship is made, the ability of the student to benefit from PhD-studies shall primarily be taken into account. In addition to devoting themselves to their studies, those appointed to doctoral studentships may be required to work with educational tasks, research and administration, in accordance with specific regulations in the ordinance. *Type of employment* Limit of tenure, four years according to HF 5 kap 7§. *Include the following documents in your application:* 1. A cover letter (maximum 1 page) with the following sections: a) Motivation (explain your interest in the project, motivation for applying, and what you hope to learn) b) Eligibility and experience (explain how you fulfil the eligibility and qualification requirements, describe your previous relevant experience and outline how you will contribute to the research group) 2. A CV (maximum 2 pages) with contact details of two referees 3. Bachelors and Masters certificates The Faculty of Medicine is a part of Lund University, and is responsible for education and research within medicine and healthcare. Our academic programs are closely linked with the healthcare system and are firmly anchored in the faculty’s strong research tradition. Our research spans a broad field within experimental preclinical research, near-patient clinical research and health sciences research. The Faculty of Medicine, with its 1,800 employees and 2,700 students in Lund and Malmö, is a knowledge-intensive meeting place for students, teachers and researchers from all over the world. We kindly decline all sales and marketing contacts. Type of employment Temporary position longer than 6 months First day of employment 220301 Salary Monthly salary Number of positions 1 Working hours 100 City Lund County Skåne län Country Sweden Reference number PA2021/3992 Contact - Gemma Atkinson, 046-2220000 Union representative - OFR/ST:Fackförbundet ST:s kansli, 046-222 93 62 - SACO:Saco-s-rådet vid Lunds universitet, 046-222 93 64 - SEKO: Seko Civil, 046-222 93 66 Published 07.Dec.2021 Last application date 09.Jan.2022 11:59 PM CET Yours Arne ----------------------------------------- Arne Elofsson Science for Life Laboratory Tel:+46-(0)70 695 1045 Stockholm University http://bioinfo.se/ Box 1031, Email: arne at bioinfo.se 17121 Solna, Sweden Twitter: https://twitter.com/arneelof Zoom: https://stockholmuniversity.zoom.us/my/arneelof/ Scholar: http://scholar.google.se/citations?user=s3OCM3AAAAAJ ORCID: 0000-0002-7115-9751 -------------- next part -------------- An HTML attachment was scrubbed... URL: From arne at bioinfo.se Thu Dec 16 13:56:26 2021 From: arne at bioinfo.se (Arne Elofsson) Date: Thu, 16 Dec 2021 13:56:26 +0100 Subject: [SocBiN] Two postdoc positions in Deep Learning and protein interactions Message-ID: Dear Sorry for cross-posting. Please spread the word that we have two postdoc positions in deep learning on protein-protein interactions *Postdoc at Stockholm University* https://www.su.se/english/about-the-university/work-at-su/available-jobs?rmpage=job&rmjob=16725&rmlang=UK *Postdoc at KTH* https://www.kth.se/en/om/work-at-kth/lediga-jobb/what:job/jobID:457741/where:4/ *Project description*Protein structure is essential for understanding their function as well as for developing drugs targeting proteins. Recently, a deep learning method that can predict the structure of most proteins was made freely available and a database with predicted structure was released. However, proteins do not act alone – they act together with other proteins. Therefore, the next major challenge is to use these types of methods for predicting protein-protein interactions. Initial studies from us have shown that it is possible to predict accurate structures of a large part of dimeric proteins using either a modified version of AlphaFold2 or AlphaFold-multimer. However, there are still many proteins that cannot be built accurately, nor are we able to always distinguish interacting from non-interacting protein pairs and to build larger complexes accurately is still an unsolved problem. In this project, we are recruiting two postdocs to leverage recent advances in the field of machine learning to build better deep-learning models for predicting protein-protein interactions and to apply these methods to biologically relevant problems. *DDLS:* The SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS) is a 12-year initiative that focuses on data-driven research, within fields essential for improving people´s lives, detecting and treating diseases, protecting biodiversity and creating sustainability. The programme will train the next generation of life scientists and create a strong computational and data science base. The program aims to strengthen national collaborations between universities, bridge the research communities of life sciences and data sciences, and create partnerships with industry, healthcare and other national and international actors. Read more at: www.scilifelab.se/data-driven. *Environment:* The Elofsson group is located at the Science for Life Laboratory. Elofsson has worked on protein structure predictions for more than two decades. He has worked on various techniques, both using machine learning and other computational techniques. His most important contributions for this work are the methods he has developed to identify the quality of protein models, Pcons and various versions of ProQ. The group consists currently of 5 PhD students and one senior researcher. Azizpour’s group is part of the KTH division of Robotics, Perception and Learning. He has extensive experience in computer vision and deep learning. The main research directions pursued in Azizpour’s group have direct relevance to this project which includes robustness and estimation of uncertainty, transfer learning including knowledge distillation techniques, non-standard deep networks e.g., graph networks and transformers, and interpretable deep learning. Furthermore, the group has extensive experience in deploying large experiments in GPU clusters. It consists of 4 PhD students, 1 postdoc, and several master students/interns. *Resources:* The groups have access to the Berzelius computer (funded by KAW). Berzelius is an NVIDIA® SuperPOD consisting of 60 NVIDIA® DGX-A100 compute nodes supplied by Atos. Each DGX-A100 node is equipped with 8 NVIDIA® A100 Tensor Core GPUs, 2 AMD Epyc™ 7742 CPUs, 1 TB RAM and 15 TB of local NVMe SSD storage. The A100 GPUs have 40 GB on-board HBM2 VRAM. Selected references: - Bryant, P, Pozzati, G. & Elofsson, A. “Improved prediction of protein-protein interactions using AlphaFold2” bioRxiv 2021.09.15.460468 (2021) doi:10.1101/2021.09.15.460468. - David F. Burke, Patrick Bryant, ....Arne Elofsson “Towards a structurally resolved human protein interaction network” bioRxiv 2021.11.08.467664; doi: https://doi.org/10.1101/2021.11.08.467664 - Mehmet Akdel, .... Arne Elofsson, Tristan I Croll, Pedro Beltrao “ A structural biology community assessment of AlphaFold 2 applications” bioRxiv 2021.09.26.461876; doi: https://doi.org/10.1101/2021.09.26.461876 - Federico Baldassarre, David Menéndez Hurtado, Arne Elofsson, Hossein Azizpour“ GraphQA: protein model quality assessment using graph convolutional networks“ Bioinformatics, Volume 37, Issue 3, 1 February 2021, Pages 360–366, https://doi.org/10.1093/bioinformatics/btaa714 - Erik Englesson, Hossein Azizpour, “Efficient Evaluation-Time Uncertainty Estimation by Improved Distillation”, ICML 2019 Uncertainty in Deep Learning workshop This is a recruitment which is part of a joint grant for two postdocs this one at Stockholm University financed by DDLS and one at KTH financed by WASP. Yours Arne ----------------------------------------- Arne Elofsson Science for Life Laboratory Tel:+46-(0)70 695 1045 Stockholm University http://bioinfo.se/ Box 1031, Email: arne at bioinfo.se 17121 Solna, Sweden Twitter: https://twitter.com/arneelof Zoom: https://stockholmuniversity.zoom.us/my/arneelof/ Scholar: http://scholar.google.se/citations?user=s3OCM3AAAAAJ ORCID: 0000-0002-7115-9751 -------------- next part -------------- An HTML attachment was scrubbed... URL: From dirk.repsilber at oru.se Mon Dec 20 09:39:40 2021 From: dirk.repsilber at oru.se (Dirk Repsilber) Date: Mon, 20 Dec 2021 09:39:40 +0100 Subject: [SocBiN] =?utf-8?q?two_years_post-doc_position_in_Statistical_Bio?= =?utf-8?q?informatics_at_=C3=96rebro_University?= Message-ID: <882cce5f-72eb-6d81-52a7-21068cdefc63@oru.se> The Functional Bioinformatics group at Örebro University offers a *two-year post-doc position in Statistical Bioinformatics*: https://www.oru.se/english/working-at-orebro-university/jobs-and-vacancies/job/?jid=20210384 The focus is on machine learning and predictive biosignature mining from OMICs data in several collaborations with partners from medical and biomedical research groups. Methods development regarding use of molecular network information for improved prediction of medical outcome and mechanistic understanding are our main research objectives. Please note the deadline: Jan 2nd 2022. Welcome to apply and forward to eligible candidates! Best Christmas greetings, Dirk -- ______________________________________________________ Dirk Repsilber Professor Functional Bioinformatics School of Medical Sciences (MV) University of Örebro S - 701 82 Örebro Sweden mobile: +46 73 270 7633 / +46 760 5161 76 / +49 160 3365511 personal: www.oru.se/personal/dirk_repsilber group: www.oru.se/forskning/forskargrupper/fg/?rdb=g206 ______________________________________________________ -------------- next part -------------- An HTML attachment was scrubbed... URL: From rbh at intomics.com Mon Dec 20 20:18:42 2021 From: rbh at intomics.com (Rasmus Borup Hansen) Date: Mon, 20 Dec 2021 20:18:42 +0100 Subject: [SocBiN] Bioinformatician, Single-cell Genomics & Target Discovery Message-ID: About the job Do you have a passion for data-driven biology to improve human health? Do you want to push the boundaries of bioinformatics to make new biomedical discoveries possible? Then we have the job for you. The job We are seeking a curious and experienced bioinformatician with a knack for translating Omics data to new biological discoveries. You will be part of the External Research & Innovation department that helps leading pharma and biotech companies derive core biological insights from biomedical big data analysis. This role is ideal for someone with an interest in lifelong learning and being at the frontiers of new bioinformatics techniques. This position exposes you to a diverse, exciting and challenging project portfolio that covers a wide range of the pharma value chain: from GWAS hits to Target Discovery to cell-type-specific Mode-of-Action. The ideal candidate has broad experience with single-cell genomics data, and an interest in applying and designing new and powerful tools for discovery of drug targets, and a passion for bringing cutting-edge research to real applications. You will play a leading role in impacting how data and bioinformatics are used in the life science and pharmaceutical industries. Responsibility, exciting challenges, and ongoing development are guaranteed in this position. Your key tasks include Lead bioinformatics analysis of large-scale genomic and biomedical datasets to address biological questions with statistical confidence Design and plan scientific projects in close collaborations with our project teams, by translating clients’ aims and needs into state-of-the-art scientific and technical solutions Disseminate findings to project stakeholders (e.g. executives and scientists) via creative visualizations, clear-cut presentations and documents Initiate and execute innovative internal R&D projects at the nexus of target discovery and single-cell genomics Contribute to the development of new efficient workflows and package pipelines for AI/ML-based bioinformatics applications Your qualifications Ph.D. degree in Bioinformatics or related fields (or MSc with at least 4-6 years of work experience) 2+ years experience working with single-cell genomics data (scRNA-seq and preferably other modalities) Knowledge and experience analyzing and integrating Omics data types (e.g. genomics, transcriptomics, epigenomics, proteomics) Excellent data science and programming skills in R and Python A solid understanding of human cell/molecular/disease biology Strong foundation in statistics and machine learning Proficiency with structuring projects and code for robust, generalizable, and reproducible data analysis Experience with Agile project management tools (e.g. GitLab) Proficiency with Linux, Git version control and high-performance computing environments Advanced data visualization skills Excellent communication and presentation skills. The ability to explain complex analytical concepts to clients and people from other fields Strong team-oriented mindset and interpersonal skills. You contribute to a diverse, open and collaborative working environment, and prioritize knowledge sharing Your extra qualifications Experience with Target Discovery and Pharmacoinformatics methods Broad experience with human genetics and the analysis of large-scale genomic association studies Knowledge of network biology approaches Broad experience with large Omics public consortia data sets and databases (e.g. GTEx, HCA, etc) Experience with pipelines and workflow management (e.g. Snakemake, Nextflow) Mentor and train team members, advising on methodologies and best practices to help overcome technical obstacles Client-facing skills and are curious about customer problems Naturally seeks creativity, innovation and excellence in your work You are not afraid to challenge the status quo and drive positive change. You contribute with a forward-thinking attitude and develop proposals to enhance existing processes and practices. You have a can-do entrepreneurial spirit and interest in commercial opportunities and collaborations. Your new team You will be a part of a fast-growing company with an agile, vibrant environment and world-class expertise. You can look forward to a strong social and collaborative company culture - built bottom-up by curious, ambitious and good humans. By joining Intomics, you will become part of a value-driven organization that works with dedication and efficiency while maintaining a high degree of flexibility and a good work-life balance. Your will work out of our attractively located office in Lyngby, North of Copenhagen, Denmark. About Intomics We’re on a mission to lead data-driven biology to improve human health. We derive core biological insights from the integration and analysis of biomedical big data. We collaborate closely with our clients in the biotech & pharmaceutical industry, and exploit the synergy between our clients’ specific disease knowledge and our unique data analytics expertise and technology. Together we make a difference for patients. This is what drives the people of Intomics. To learn more about Intomics visit https://www.intomics.com/. Contact and application Please send your motivated application, CV and references to applications-2105 at intomics.com no later than January 14th, 2022. Applications will be reviewed on an ongoing basis, so do not hesitate to apply. Questions can be directed to Pascal N. Timshel, Team Leader Target Discovery & Single-cell Genomics Your application will be treated in accordance with our policies for processing of personal data incorporating the General Data Protection Regulation of the EU. https://www.linkedin.com/jobs/view/2840741037/ https://www.intomics.com/open-vacancies/bioinformatician-single-cell-genomics-target-discovery/ -------------- next part -------------- An HTML attachment was scrubbed... URL: