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Artifical Intelligence in Drug Discovery

Am Institut für Pharmazie und Molekulare Biotechnologie (IPMB) der Universität Heidelberg ist in der Abteilung Medizinische Chemie baldmöglichst eine Stelle als Akademische/r Mitarbeiter/in (Doktorand/in, m/w/d) zu besetzen. Thema: Maschinelles Lernen in der Wirkstoffentwicklung. Wünschenswert ist ein starkes Interesse und idealerweise Vorkenntnisse in instrumenteller Analytik (Massenspektrometrie) und Programmiersprachen (z.B. MATLAB, Python) sowie ein naturwissenschaftlich-technischer Studienabschluss (Chemie, Biotechnologie, Pharmazie, (Bio-) Informatik, Physik und vergleichbar). Die Vergütung erfolgt nach TV-L E13 50%. Die Stelle ist zunächst auf zwei Jahre befristet. Bewerbungsschluss ist der 31.10.2019. Weitere Informationen zu Thema und Bewerbungsprozess finden Sie online hier (https://adb.zuv.uni-heidelberg.de/info/INFO_FDB$.startup?MODUL=LS&M1=1&M2=0&M3=0&PRO=28025).


Links:
Weitere Informationen:
https://adb.zuv.uni-heidelberg.de/info/INFO_FDB$.startup?MODUL=LS&M1=1&M2=0&M3=0&PRO=28025

Postdoctoral Researcher in data analysis & methods development

For a project in crystallographic data analysis and methods development,
the Thorn Laboratory at the University of Würzburg, Germany, is looking
for a

POSTDOCTORAL RESEARCHER (m/f/d)

to uncover pitfalls in the measurement and processing of XFEL, neutron
and conventional single-crystal diffraction data. She or he will develop
new diagnostics in AUSPEX (www.auspex.de) using machine learning,
practical experiments and statistical analysis and establish new best
practices with major European diffraction facilities. We are looking for
someone with a good working knowledge of statistical analysis, Python
and C++ who is an excellent communicator and likes to travel. Previous
experience in crystallography and machine learning is a bonus.
We offer a position at the University of Würzburg, the birthplace of
X-rays, with a competitive salary, benefit package, career and family
support. Women are particularly encouraged to apply.

For more details, see:
https://www.uni-wuerzburg.de/fileadmin/43020000/2019/Stellenanzeige_PostdocThorn_Sep_2019_final_Auslage.pdf
https://www.uni-wuerzburg.de/rvz/forschung/assoziierte-forschungsgruppen/ag-thorn/

If you have any questions, please email This email address is being protected from spambots. You need JavaScript enabled to view it..

Links:
Full advertisement:
https://www.uni-wuerzburg.de/fileadmin/43020000/2019/Stellenanzeige_PostdocThorn_Sep_2019_final_Auslage.pdf
Group homepage:
https://www.uni-wuerzburg.de/rvz/forschung/assoziierte-forschungsgruppen/ag-thorn/

PhD candidate in crystallographic methods development

For a project in crystallographic methods development, the Thorn
Laboratory at the University of Würzburg, Germany, is looking for a

PHD CANDIDATE (m/f/d)

Our lab develops new methods for macromolecular X-ray crystallography
and Cryo-EM. In this exciting PhD project you will improve how well we
understand, measure and model macromolecular crystal structures using
practical experiments and big data analyses. We are looking for a good
communicator with skills in crystallography and programming. Any
previous experiences in machine learning, biochemistry, image or
statistical data analysis are a bonus. We offer a 36-month full- or
part-time position with a competitive salary, embedded in the Würzburg
Graduate School for Life Sciences (GSLS).

For more details, see:
https://www.uni-wuerzburg.de/fileadmin/43020000/2019/Stellenanzeige_PhD_Thorn_September_2019_final_Auslage.pdf
https://www.uni-wuerzburg.de/rvz/forschung/assoziierte-forschungsgruppen/ag-thorn/

If you have any questions, please email This email address is being protected from spambots. You need JavaScript enabled to view it..

Links:
Full advertisement:
https://www.uni-wuerzburg.de/fileadmin/43020000/2019/Stellenanzeige_PhD_Thorn_September_2019_final_Auslage.pdf
Group homepage:
https://www.uni-wuerzburg.de/rvz/forschung/assoziierte-forschungsgruppen/ag-thorn/

PhD student position (TVH-E13 65%) in Bioinformatics [the University of Marburg and the University of Giessen II]

The candidate will be responsible for the development of bioinformatics software to improve the comparability and reproducibility of state of the art methods to evaluate efficient data storage. That is to say, encoding information in biological molecules or chemical compounds. The action of encoding and decoding information is a process that we perform on a daily basis. Language is a great example as words carry different meanings. There exists many levels of processing information, the successful candidate will examine information theory metrics (e.g., compression ratio), error correction, and decoding accuracy (e.g., parity checks) for a quantitative assessment of information processing. A foundational aspect of this project is the creation of an evaluation framework that integrates state of the art methods for text mining (e.g., Markov chains, Long short-term memory or LSTM, etc). Her/His efforts include but are not limited to developing novel algorithms, implementing different state of the art methods into an open source framework, and maintaining a code base to benefit both the community and the research project. 

In the research project MOSLA, the University of Marburg and the University of Giessen will jointly develop novel approaches and solutions for long-time archives based on molecular and chemical stor-age systems. Besides the technical solutions of data storage, they will also research in (de-)coding of information for long-time storage, which will be achieved by a combination of genetic and chemical information encoding. The project is funded by the Hessian Ministry for Science and Arts. 

 

Links: https://synmikro.com/assets/content/Downloads/Ausschreibungen/fb12-0024-MOSLA-wmz-111019-engl.pdf

PhD student position (TVH-E13 65%) in Bioinformatics [University of Marburg and the University of Giessen]

The candidate will be responsible for the development of bioinformatics software, novel algorithms, and visualizations to depict the effect of weighing in reading frame and genomic patterns in the de-coding of information stored in biological molecules or chemical compounds. The desired end result is to visualize the qualitative and quantitative improvement of decoding when using different encod-ing/decoding strategies. The successful candidate will examine possible patterns that range from naturally occurring sequences to repeats, or functional patterns (secondary structure), and define successful strategies of encoding/decoding. In turn, these may be used as quality control checks once PCR amplification and sequencing have been completed. A foundational aspect of this project is the creation of adapted representations and algorithms to account for different encoding/decoding strategies. Her/His efforts include but are not limited to developing novel algorithms, implementing a visualization framework, and maintaining a documentation and a code base to benefit both the com-munity and the research project. 

In the research project MOSLA, the University of Marburg and the University of Giessen will jointly develop novel approaches and solutions for long-time archives based on molecular and chemical stor-age systems. Besides the technical solutions of data storage, they will also research in (de-)coding of information for long-time storage, which will be achieved by a combination of genetic and chemical information encoding. The project is funded by the Hessian Ministry for Science and Arts. 


Links: https://synmikro.com/assets/content/Downloads/Ausschreibungen/fb12-0023-MOSLA-wmz-111019-engl.pdf

Master internship in Bioinformatics

Location: EMBL Rome, Italy
Category: Master internship
Duration: Minimum of 6 months, up to one year
Closing Date: October 15th 2019
Starting Date: Can be arranged with the selected candidate
 
The EMBL Epigenetics and Neurobiology Unit in Monterotondo (near Rome, Italy) is seeking a highly motivated student to join the Bioinformatics Services of EMBL Rome and the Boulard group for a Master internship.

Project

Epigenetics define biochemical modifications that are independent of the DNA sequence such as DNA methylation and histone modifications. Methylation of specific histone residues has been shown to influence gene expression. Abnormalities in histone modifications or transcription factor (TF) binding are frequently observed in cancer.
Innovative clinical trials targeting writers or erasers of histone modifications are currently under development. However, the gold standard method for epigenomic profiling, namely ChIP-seq, has failed to show differences in chromatin modification upon treatment by these new epi-drugs. Over 30 years ago, the ChIP protocol was introduced and has been widely-used by the community to screen for TFs or histone modifications genome-wide without spike-in controls. Recent developments and enhancements of ChIP-seq with enzyme-tethering and spike-in methods such as DamID, ChEC-seq, or Cut&Run, both at bulk and single-cell level offer investigation of genomic loci at an unprecedent precision.
 
The recent genomic revolution arising from these technologies however still lack solid bioinformatics foundations and benchmarking due to their recent development. The selected candidate, under the supervision of Nicolas Descostes and Mathieu Boulard, will be in charge of developing methodologies for processing and analyzing Cut&Run and Cut&Tag data. The work will involve benchmarking and analysis of publicly available but also internally produced data sets. These methodologies will have to be integrated in a pipeline. The candidate will have the opportunity to learn how to perform bioinformatics using one of the most powerful High Performance Computing (HPC) system in Europe but also, according to progression, to be initiated to the use of singularity dockers and conda environment. The work will be performed with Snakemake.
 
Profile
 
Background in Bioinformatics, Physics, Mathematics, Computer Sciences or other related disciplines are welcome.
The Candidate should have a solid training in programming (at least two-three courses of 30 hours with equivalent time of coding). The candidate will have to demonstrate that he or she conducted projects (in Java, C, R, Python or others) within the context of classes at University. Experience in project in R will be a plus.
Knowledge in genome biology would be a key advantage.
Good communication skills in English is compulsory.

Benefit

The selected candidate will be provided a small stipend and accommodation.

Application

CV and motivation letter should be sent to This email address is being protected from spambots. You need JavaScript enabled to view it..

Interdisciplinary Ph.D. Positions in Scientific Computing, Data Science and Physics

DASHH is a recently established, interdisciplinary graduate school that offers challenging Ph.D. topics at the interface of the natural sciences, applied mathematics and data and computer science. DASHH involves several research institutions and universities in the multifaceted city of Hamburg, Germany.

DASHH is looking for excellent and highly qualified Ph.D. candidates, interested to work on data-driven research in physics, chemistry, applied mathematics, computer science or structural biology.

We offer:

  • Interdisciplinary research in the natural sciences and computer/data science or applied mathematics
  • Research at world leading large-scale research facilities (PETRA III, FLASH, European XFEL, LHC)
  • Attractive, interdisciplinary thesis topics
  • Excellent working conditions at an international, vibrant and inspiring research campus
  • Close supervision and support by a panel of established professors and scientists
  • Training in transferable skills and career development
  • Work contract at the level of the German TV-L13 (100%) salary scheme for 3 year

Requirements:

We are looking for highly motivated students with an excellent academic background in the natural sciences, engineering sciences, informatics or applied mathematics. The candidates should bring a strong interest to work on highly interdisciplinary topics, should be team oriented and have a strong background in programming. For more information see: https://www.dashh.org

Application Deadline:

December 1st, 2019

DASHH is a joint venture of the Deutsches Elektronen Synchrotron (DESY), the Universität Hamburg (UHH), the Technische Universität Hamburg (TUHH), the Helmut Schmidt Universität (HSU), the Helmholtz Zentrum Gesthacht (HZG), the Helmholtz Zentrum für Infektionsforschung (HZI), Max Planck Institut für Struktur und Dynamik der Materie (MPSD) and European XFEL GmbH.

Identification of genomic differences from whole-genome alignments (Klau/Schneeberger labs)

Genome sequences are key resources to understand functional processes and divergent trait evolution within and between different species. Within http://ceplas.eu, many high-quality genome assemblies of closely related species of the Brassicaceae and other plant families are being generated. This makes it possible, in principle, to reveal intra-family similarities and structural variations from pairwise whole-genome alignments (WGA) as a major step towards family pangenome representations. However, even though efficient whole-genome alignment solutions exist there are no computational approaches that would annotate all genomic differences including the obvious hierarchy ranging from small single nucleotide changes to large complex rearrangements. The project will therefore extend SyRI, an existing algorithm for genome-wide structural rearrangement identification to solve this efficiently.

Qualifications needed: good algorithmic background, programming skills, basic knowledge in bioinformatics, Plus: experience with genomic data and/or plant genomics

Contact persons: Gunnar Klau (HHU), Korbinian Schneeberger (MPI)

PhD position “Machine-learning approaches for data integration and patient stratification in schizophrenia and comorbid diseases”

The Health Data Science Unit (HDSU, www.hdsu.org) is a newly created unit of the BioQuant and medical Faculty of the University Heidelberg, which focuses on research topics related to digital health and the integration of clinical and genomic datasets.

The recently funded COMMITMENT project (COMorbidity Modeling via Integrative Transfer machine-learning in MENTal illness), in which HDSU is leading one work-package, will establish an interdisciplinary research consortium for the identification of molecular hallmarks of schizophrenia and comorbid somatic illnesses, such as diabetes or cardiovascular diseases. The identification of shared and distinct biological profiles will allow disentangling patient heterogeneity and provide the basis for objective tools for personalized clinical management of psychotic disorders.

The HDSU will lead the work-package on data integration, signature extraction and transfer learning over cohorts of

In this context, we are looking for a PhD student with a focus on the following points:

- Extension of existing matrix factorization (MF) approaches for the integration of heterogeneous datasets;
- Comparison of neural network models and MF methods for the definition of molecular signatures;
- Extraction of molecular signatures using transfer learning approaches

 

We are looking for a candidate with the following qualifications:

- A master degree in the field of computational biology or applied mathematics with a focus on statistical learning
- Good programming skills and first experiences in the field of machine-learning
- An interest in working in an interdisciplinary field involving clinicians, biologists, statisticians and computer scientists
- Good communication skills

We are offering

- An exciting, excellent and highly multi-disciplinary research environment on the campus of Heidelberg University, Germanys oldest university
- Payment according to German TV-L E13 (65%)
- A superb living environment in Heidelberg and surroundings.

Application letters and CVs (as pdfs), together with contact information of two referees should be sent by mail to This email address is being protected from spambots. You need JavaScript enabled to view it.

Links: https://www.hdsu.org

Wissenschaftlicher Mitarbeiter (w/m/d) Fachrichtung Biologie, Bioinformatik, Statistik [Tierärztliche Hochschule Hannover]

Am Institut für Tierzucht und Vererbungsforschung der Tierärztlichen Hochschule Hannover ist zum

nächst möglichen Termin eine Stelle als

 

wissenschaftlicher Mitarbeiter (w/m/d)

(Fachrichtung Biologie, Bioinformatik, Statistik)

 

mit 75% der vollen Arbeitszeit zu besetzen. Die Stelle ist auf drei Jahre befristet. Ein Promotionsvorhaben

auf der Stelle wird unterstützt und ausdrücklich erwünscht.

 

Aufgaben sind die die Mitarbeit in aktuellen Forschungsaktivitäten der Arbeitsgruppe „Genomics and

Bioinformatics of Infectious Diseases“. Dazu zählen vor allem die Weiterentwicklung und Anwendung

von statistisch-bioinformatischen Methoden für die Analyse von High-Throughput-Sequenzdaten und

High-Throughput-Genexpressionsdaten (NGS-, Microarrays-Daten).

 

Voraussetzung für eine Bewerbung ist ein abgeschlossenes wissenschaftliches Hochschulstudium

mit Masterabschluss in Biologie, Bioinformatik, Statistik oder einem vergleichbaren Fach.

Die Vergütung erfolgt nach E 13 TV-L.

 

Schwerbehinderte Bewerberinnen und Bewerber werden bei gleicher Eignung vorrangig berücksichtigt.

Bitte senden Sie Ihre aussagekräftige Bewerbung per E-Mail bis spätestens 20.10.2019 an Herrn Prof.

Dr. Klaus Jung (This email address is being protected from spambots. You need JavaScript enabled to view it.), Institut für Tierzucht und Vererbungsforschungs, Tierärztliche

Hochschule Hannover. Weitere Auskünfte zu der Stelle werden gerne über diese E-Mail-

Adresse erteilt.

 

Ihre personenbezogenen Daten werden vertraulich behandelt (www.tiho-hannover.de/ds-bew).