JOB: postdoc in machine learning applied to cancer @SISSA, Trieste
we have an opening for one 2-years (renewable) postdoctoral position working on machine learning for hematological cancer data in our group at the International School of Advanced Studies in Trieste. Essential: knowledge of statistical/ machine learning methods applied in a scientific context. Desirable: familiarity with bioinformatics methods for sequencing data. Applications from women and under-represented groups are particularly welcome. Please email me before making an application if you have any questions.
Deadline and link: 27/02/2024
About the job: We have recently obtained a substantial grant from AIRC, the Italian cancer research charity. The project is in collaboration with Humanitas University Hospital in Milan and the University of Bologna, and aims to integrate diverse data types (clinical, genomic, transcriptomic and epigenomic) to support clinical decision making, particularly in data poor situations. The approach combines Bayesian methods and advanced ML techniques (GNNs, VAEs etc) as well as methods from interpretable AI.
About SISSA: SISSA is an international PhD school located in Trieste, north-eastern Italy. It hosts about 100 PIs and 500 researchers (PhD and postdocs) in an interdisciplinary setting focussed on physics, mathematics and neuroscience. SISSA established a data science group in 2020 working on methodological and scientific applications of machine learning, see here https://datascience.sissa.it.
About Trieste: Trieste is a city of about 200K inhabitants located on the northernmost point of the Mediterranean Sea, close to the border with Slovenia. Long the port city of the Austro-Hungarian empire, it is a beautiful city combining a mediterranean and Central European character. It is regularly listed as one of the top Italian cities in terms of quality of life, with easy access to the Alps, the Adriatic Sea, and a relatively low cost of living.
The Timr group (http://www.stepantimr.com) at the J. Heyrovsky Institute of Physical Chemistry in Prague is seeking a highly motivated postdoctoral associate to work on multi-scale modeling of dynamic enzyme assemblies.
Our research group focuses on the computer simulation of the cell interior. Using multi-scale computational models, we aim to elucidate the physical and chemical mechanisms governing the organization of metabolic pathways in living cells. Supported by the Lumina Quaeruntur Award and a grant from the Czech Science Foundation, our team is integrated into the interdisciplinary Department of Computational Chemistry. This department bridges the physical chemistry and biophysics of proteins and membranes with theoretical enzymology and spectroscopy.
The postdoctoral associate will develop mesoscopic computational models to understand the roles of dynamic enzyme assemblies in metabolic regulation. The goal is to develop and implement a novel framework that will integrate detailed insights from all-atom and coarse-grained MD simulations with larger-scale reaction-diffusion models of dynamic enzyme assemblies. This work will be an important contribution to our mechanistic understanding of metabolic pathway organization in cells.
The initial contract period is for one year with the possibility of extending up to four years. The position will remain open until a suitable candidate is found.
- PhD in a quantitative field, such as Mathematical/Computational Biology, Biophysics, Chemical Engineering, or Applied Mathematics.
- Strong skills in developing and implementing mathematical models.
- Proficiency in programming and scripting languages (e.g., Python, C++) for model development and data analysis.
- Excellent communication and collaboration skills.
Experience in kinetic modeling of enzymes and metabolic pathways, reaction-diffusion modeling, classical MD simulations, and Markov models will be considered an asset.
To apply, please send your CV, a list of publications, a motivation letter, and contact information for two references to firstname.lastname@example.org and email@example.com. Please include SC2023_37 in the email subject line. For any inquiries, contact firstname.lastname@example.org.
Starting date: The position is available immediately.
Type of contract: Temporary
Job status: Full time
Position of Assistant Professor in Applied Mathematics and Statistics
Department : Engineering and Process Sciences Department (DSIP)
Discipline: Applied Mathematics and Applications of Mathematics
CNU n° 26/ CNECA 3 (Ministère de l'Agriculture et de la Souveraineté alimentaire)
A position for an assistant professor (Maître de conferences/MCF) in applied mathematics and statistics is likely to be published in spring 2024 at the Institut Agro, Dijon. The research activities will be carried out within the UMR Agroécologie (INRAE/University of Burgundy/Institut Agro), Pôle MICSOL, in connection with the 'microbiology and ecosystem functions of soils' theme. The profile sought is that of a candidate at the interface between statistics in its contemporary data science aspects and mathematical modelling for life and environmental sciences.
Teaching activities will take place within the Engineering Sciences and Processes Department. The MCF will be involved in initial engineering training (agronomy and agri-food pathways) and apprenticeships as part of core and specialised teaching. There will also be opportunities to take part in international masters courses, such as those run by SFRI's 'Integrate' Graduate School 'Transbio' or the FORTHEMICROBES international masters course run by the FORTHEM European Alliance. The person recruited will need to have a general knowledge of both the mathematical/theoretical and practical aspects of statistics, as well as standard software and languages (R, Python), enabling them to adapt their teaching to a variety of specialist and non-specialist audiences.
Both the research and teaching aspects of this post are in line with strategic priority 5 "Data science' in the research strategy of the Institut Agro Dijon.Through its application aspects in soil microbiology, in particular the dimension linked to the evaluation of the quality of the microbial component of agroecosystems, this position also contributes to Axis 3 "Natural and controlled microbial ecosystems", a differentiating research topics of the Institut Agro Dijon.
DSIP Director: Ludovic Journaux
Director of UMR Agroecology Fabrice Martin
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