January 2024 - FG-VIS

Last Reminder >>> Open Position as Head of the Junior Research Group "Human-centered AI" at CAIMed, PLRI, Hannover Medical School, Germany
by Oeltze-Jafra.Steffen＠mh-hannover.de 29 Jan '24

29 Jan '24

**************************************************************************************** Apply until January, 31st for a Group Leader Position in Visual Analytics&AI **************************************************************************************** Hannover Medical School (MHH) is one of the locations of the newly established Lower Saxony research center for artificial intelligence and causal methods in medicine - CAIMed<https://caimed.de/en/>. At CAIMed, international teams research and develop innovative methods at the interface between AI and personalized medicine and contribute to tackling common diseases such as cancer, cardiovascular diseases and infections. CAIMed at MHH offers a position as Head of the Junior Research Group "Human-centered Al"<https://caimed.de/en/forschung/ki-entscheidungen/menschzentrierte-ki/> to be filled at the earliest possible date. If you are keen on establishing a research team (head + 2 PhDs + 1/2 secretary) that works on blending visual analytics and AI for the analysis of medical (imaging) data, apply until January, 31st through the job portal of MHH: EN: https://mhh.hr4you.org/job/view/2144/head-f-d-m-of-the-caimed-junior-resear… DE: https://mhh.hr4you.org/job/view/2142/leitung-w-d-m-der-caimed-nachwuchsfors… The research group will be associated with the Peter L. Reichertz Institute for Medical Informatics (PLRI) of TU Braunschweig and MHH. PLRI, one of the largest medical informatics institutions in Germany, offers excellent research opportunities. We collaborate in interdisciplinary projects with health care centers, research institutes, enterprises and public organizations on a regional, national and global level. Your tasks * Development and establishment of the junior research group * Developing new human-centered AI approaches together with clinical partners * Support in the acquisition of third-party funding * Publication of high-quality scientific publications * Involvement in national and international research networks * Collaboration in university teaching and supervision of students more details: CAIMed. <https://caimed.de/en/forschung/ki-entscheidungen/menschzentrierte-ki/> Our requirements * PhD in computer science, data science, business, medical, bio- or business informatics, mathematics or a comparable degree program * Extensive research experience in (at least) one of the following areas * Visual analytics of medical data * AI-based medical image analysis * Clinical decision support systems * Medical data science and/or knowledge engineering * Above-average publication profile * Very good oral and written English skills * Willingness to work closely with an interdisciplinary project team * Initiative and a results-orientated working style * Experience in acquiring third-party funding and management are an advantage We offer * a full-time position with 38.5 hours per week, initially limited until 31 October 2028, with one of the largest employers in the state of Lower Saxony * remuneration in accordance with TV-L in EG 14-15, taking into account the individual qualification, with the benefits of the public sector (e.g. company pension scheme and additional insurance through VBL) * increased flexibility through partially mobile work or teleworking * the opportunity to acquire your own third-party funding and to further develop your own academic qualifications (habilitation) and leadership skills * Work in a motivated, team-orientated and international research institute * Personal and professional development opportunities - supported by our diverse internal and external training and further education programs * a job ticket for local public transport and other diverse offers * an excellent range of sports, counselling and prevention programs - because your health is important to us -- Prof. Dr.-Ing. Steffen Oeltze-Jafra Peter L. Reichertz Institute for Medical Informatics of TU Braunschweig and Hannover Medical School Medical Information Systems, Campus Hannover OE 8420, room: M02-S0-0190, Karl-Wiechert-Allee 3, 30625 Hannover, Germany tel: +49 511 532-80830, fax: +49 511 532-5297 oeltze-jafra.steffen(a)mh-hannover.de<mailto:oeltze-jafra.steffen@mh-hannover.de> [www.plri.de]www.plri.de<http://www.plri.de>

1 0

Last Reminder >>> [PhD Position Opening] Prae-doc position on Visual Analytics and Information Diffusion @ TU Vienna – 30/40 hrs (m/f/d)
by Miksch Silvia 28 Jan '24

28 Jan '24

## Apologies if you receive multiple copies of this message ## --------------------------------------------------------------- ** FUNDED PHD POSITION AT TU VIENNA ** --------------------------------------------------------------- Funded PhD position within the ViSual ANalytics for Event-based Diffusion on Networks (SANE) project @ TU Wien f/m/d (30-40h) We are hiring a talented PhD candidate in an international project on the visual analytics of complex diffusion processes over temporal networks. You will work in the context of SANE, a project held by TU Vienna (Austria), the University of Cologne (Germany) and the University of Newcastle (United Kingdom). This project arrangement gives you unique career opportunities, including student exchanges abroad, regular meetings with researchers from the other institutions participating to the project. We are looking for a PhD candidate to work from the TU Wien, at the Institute of Visual Computing and Human-Centered Technology, in the Research Unit of Visual Analytics. We offer a position as project assistant (prae-doc) limited to 3 years for 30 hours/week (that can beextended to 40). Gross annual (monthly) salary of Euro 43,650 (2,464.80) according to FWF regulations. In this position, you will begin your doctoral journey studying problems related to the topic of event-based(or “temporal”) network visualization. In Event-based networks, the time coordinates where the nodes and the edges are “active” are an explicit element of the representation, differently from traditional timeslicing where a time structure is imposed over the input data. You will apply these concepts to the problem of Information Diffusion. Information Diffusion studies how “information” flows and spreads through an underlying network, and has been used to model, simulate, and predict natural and human-made phenomena in countless different domains (e.g., pathogen spread, malware outbreak in computer networks, viral marketing, etc.). However, little research has been done on this problem within the context of visualization. Wanna know more? Check the project description and complete job posting at https://www.cvast.tuwien.ac.at/projects/sane --------------------------------------------------------------- Deadline for applications: 29 January 2024 Expected start: March 2024 --------------------------------------------------------------- Questions? You can reach me at Alessio.arleo(a)tuwien.ac.at

1 0

[Open for Submissions] 1st Workshop on Visual Process Analytics (VIPRA 2024) - Co-Located EuroVis 2024
by Arleo, Alessio 22 Jan '24

22 Jan '24

##################################################### 1st Workshop on Visual Process Analytics (VIPRA 2024) https://vipra-workshop.github.io/homepage/ ##################################################### Call for Papers ---------------- The 2024 Workshop on Visual Process Analytics (Vipra 2024) is the 1st annual workshop that provides an opportunity for participants to discuss state-of-the-art event visualization and process mining and learn how both techniques can mutually benefit each other. In this workshop we aim to bring together researchers from both Visual Analytics and Process Mining, to learn, create a common language, spark collaborations, and advance both fields. Process Mining is a data-driven discipline that focuses on extracting valuable insights and knowledge from the vast amount of event data generated within organizations. It involves the discovery, analysis, and improvement of process models by leveraging techniques from data science, machine learning, and data analytics. By examining event logs and historical data, process mining aims to provide a clear, objective view of how processes actually operate, identifying bottlenecks, deviations, and opportunities for optimization. In turn, this supports organizations in making more data-informed decisions, and enhance operational efficiency. Visual analytics is an interdisciplinary field that combines data visualization, analytical techniques, and interactive interfaces to help people make sense of complex and often large datasets. It focuses on using the power of visual representations to facilitate data exploration, pattern recognition, and decision-making. By enabling users to interact with data through graphical interfaces, visual analytics promotes a deeper understanding of information, uncovers hidden insights, and supports the detection of trends, anomalies, and relationships that might be challenging to discern through traditional data analysis methods alone. We believe that process mining and visual analytics can mutually benefit each other. Until now, there has been limited interaction between the two fields, despite their shared objectives. In process mining, the emphasis has traditionally been on data extraction and process discovery, often neglecting the visualization aspect, whereas in visual analytics, event visualization efforts have often overlooked the wealth of process mining techniques that can enhance visualizations and analysis. Bridging this gap and fostering collaboration between the two fields will not only lead to more informed, efficient, and data-driven improvements in various domains but also advance the research and innovation in both process mining and visual analytics, ultimately contributing to a more holistic and integrated approach to understanding and optimizing complex processes. Topics and Scope ---------------- We encourage submissions from all areas on the intersection of visual analytics and process mining. The 2024 Workshop on Visual Process Analytics will cover a range of topics exploring the intersection of PM and VA including (but not limited to): - VA to support exploration and comparison of discovered process models - VA to support the comparison of event logs and process models, e.g., in conformance checking - VA to support the generation of hypotheses about the business process and the identification of process improvement ideas - VA to represent temporal and spatial uncertainty in PM models - Research challenges, pitfalls, and opportunities related to the intersection of VA and PM - The role of AI in PM, and how Visualization and explainable-AI solutions can support model comprehension, exploration, and refinement Paper Submission, Publication, and Format Guidelines -------------------------------------- We will accept short papers with up to 5 pages plus one page of references (5 + 1). We encourage a diverse range of submissions and demonstrations in any of the short paper types listed below: - Application/Case-study papers (format: 5 + 1) - Research papers (format: 5 + 1) - Position papers and system demos papers (format: 2 + 1) All material will be submitted via the Precision Conference System (PCS): https://new.precisionconference.com/submissions For all submissions, please use the EuroVis 2024 LateX2e Style. On Overleaf, this template can be imported easily by selecting "New Project" -> "Upload Project" and uploading the zip file. Use EGAuthorGuidelines-eurovis24-short.tex for your submission: https://medialib.cmcdn.dk/medialibrary/80234312-1C55-406C-86A7-410099EB2739… Accepted papers will be included in the EuroGraphics Digital Library and will be assigned a DOI as fully citable publications. Contact vipra.workshop at gmail.com if you have any questions or visit https://vipra-workshop.github.io/homepage/ Important Dates --------------- - Deadline for submission: March 1st, 2024 - Notification of acceptance: April 12th, 2024 - Camera-ready papers due: April 26th, 2024 - Vipra 2024 Workshop: May 27th, 2024 (in conjunction with EuroVis 2024) All submission deadlines are at 23:59 GMT on the date indicated. Organizers ---------- Alessio Arleo, TU Wien Stef van den Elzen, Eindhoven University of Technology Tatiana von Landesberger, Universität Köln Luise Pufahl, TU München - Heilbronn Jana-Rebecca Rehse, Universität Mannheim Francesca Zerbato, Universität St. Gallen

1 0

[PhD Position Opening] Prae-doc position on Visual Analytics and Information Diffusion @ TU Vienna – 30/40 hrs (m/f/d)
by Arleo, Alessio 08 Jan '24

08 Jan '24

--------------------------------------------------------------------------------- ** REMINDER: FUNDED PHD POSITION AT TU VIENNA ** --------------------------------------------------------------------------------- Funded PhD position within the ViSual ANalytics for Event-based Diffusion on Networks (SANE) project @ TU Wien f/m/d (30-40h) We are hiring a talented PhD candidate in an international project on the visual analytics of complex diffusion processes over temporal networks. You will work in the context of SANE, a project held by TU Vienna (Austria), the University of Cologne (Germany) and the University of Newcastle (United Kingdom). This project arrangement gives you unique career opportunities, including student exchanges abroad, regular meetings with researchers from the other institutions participating to the project. We are looking for a PhD candidate to work from the TU Wien, at the Institute of Visual Computing and Human-Centered Technology, in the Research Unit of Visual Analytics. We offer a position as project assistant (prae-doc) limited to 3 years for 30 hours/week (that can beex-tended to 40). Gross annual (monthly) salary of Euro 43,650 (2,464.80) according to FWF regulations. In this position, you will begin your doctoral journey studying problems related to the topic of event-based (or “temporal”) network visualization. In Event-based networks, the time coordinates where the nodes and the edges are “active” are an explicit element of the representation, differently from traditional timeslicing where a time structure is imposed over the input data. You will apply these concepts to the problem of Information Diffusion. Information Diffusion studies how “information” flows and spreads through an underlying network, and has been used to model, simulate, and predict natural and human-made phenomena in countless different domains (e.g., pathogen spread, malware outbreak in computer networks, viral marketing, etc.). However, little research has been done on this problem within the context of visualization. Wanna know more? Check the project description and complete job posting at https://www.cvast.tuwien.ac.at/projects/sane --------------------------------------------------------------- Deadline for applications: 29 January 2024 Expected start: March 2024 (Negotiable) --------------------------------------------------------------- Questions? You can reach me at Alessio.arleo(a)tuwien.ac.at<mailto:Alessio.arleo@tuwien.ac.at>

1 0