德国亥姆霍兹国家研究中心2022年招聘博士后（机器学习用于动物迁移分析）

德国亥姆霍兹国家研究中心2022年招聘博士后（机器学习用于动物迁移分析）

PostDoc (F/M/D) Machine Learning For Animal Movement Analysis

Helmholtz-Zentrum Dresden-Rossendorf

Description

For any questions, do not hesitate to ask: Dr. Justin Calabrese Tel.: +49 3581 37523 71, Dr. WeronikaSchlechte-Welnicz Tel.: +49 3581 37523 72

Place of work: Görlitz

Working hours: 39 h/week

Deadline: 19 August 2022

Online application English / German Job-Id: 2022/121 (1465)

The HZDR is committed to equal opportunity employment and we strongly encourage applications from qualified female candidates. We also carefully consider all applications from job candidates with severe disabilities.

Helmholtz-Zentrum Dresden-RossendorfBautznerLandstraße 400 01328 Dresden

PostDoc (f/m/d) Machine learning for animal movement analysis

Through cutting-edge research in the fields of ENERGY, HEALTH and MATTER, Helmholtz-Zentrum Dresden-Rossendorf (HZDR) solves some of the pressing societal and industrial challenges of our time. Join our 1.400 employees from more than 50 nations at one of our six research sites and help us moving research to the next level!

The Center for Advanced Systems Understanding (CASUS) is a German-Polish research center for data-intensive digital systems research. CASUS was founded in 2019 in Görlitz and conducts digital interdisciplinary systems research in various fields such as earth systems research, systems biology and materials research.

As part of the Institute, the Department of Earth System Science invites applications as PostDoc (f/m/d) Machine learning for animal movement analysis.

The position will be available from 1 October 2022. The employment contract is limited to two years.

Job Background and Scope:

The successful candidate (f/m/d) will be part of an internationally renowned team that focuses on developing analytical method and software for animal movement data. The candidate's work will broaden the focus of the group's efforts to encompass the application of ML techniques to problems including, but not limited to, the classification of individuals as range resident (or not), the identification of behavioral states in tracking time series, and the integration of multiple data streams (e.g., GPS location data and accelerometer data). This research will leverage a large, multi-species tracking dataset for both training and cross-validating the ML algorithms.

Your tasks:

Design, implement and compare a range of machine learning (ML) techniques for solving challenging problems in movement ecology

Develop open-source software implementing the successful ML approaches for a broad user audience

Identify analysis problems in movement ecology that are particularly amenable to ML approaches

Publish results in peer-reviewed, academic journals

Present results at scientific meetings

Your profile:

PhD degree in Machine Learning, Statistics, Data Science, Quantitative Ecology, Physics or a related field

Experience in developing and implementing modern machine learning methods

Advanced programming and package development skills in R

Prior experience working with animal tracking data is advantageous but not required

Excellent communication skills in English in a professional context (presentation of research results at scientific meetings, colloquial discussions, manuscript writing)

Evidence of the ability to publish results in top peer-reviewed journals

Our offer:

A vibrant research community in an open, diverse and international work environment

Scientific excellence and extensive professional networking opportunities

The employment contract is limited to two years

Salary and social benefits in accordance with the collective agreement for the public sector (TVöD-Bund) including 30 days of paid holiday leave, company pension scheme (VBL)

We support a good work-life balance with the possibility of part-time employment and flexible working hours

Numerous company health management offerings

Kindly submit your completed application (including cover letter, CV, diplomas/transcripts, etc.) only via our Online-application-system.

Apply here Jetztbewerben