Doctoral Researcher in Optimization of Mineral Resource Modelling Using Machine Learning Approaches

University of Oulu Faculty of Technology

Finland

Doctoral Researcher in Optimization of Mineral Resource Modelling Using Machine Learning Approaches

We at the University of Oulu work as part of the international science community to produce new scientific information and science-based solutions. We are committed to educate future pioneers to build a more sustainable, intelligent and humane world. Creating new, taking responsibility and succeeding together are values that build a strong foundation for all our actions. We offer a working environment where individuals can cultivate their skills, do meaningful work, and develop professionally. Our university's several specialized research and service units enable extensive and diverse development and career opportunities for experts in various fields.

We are looking for a Doctoral Researcher for the Horizon Europe funded SEMACRET (Sustainable Exploration for Orthomagmatic (critical) raw materials in the EU: Charting the road to the green energy transition project. The SEMACRET consortium includes 16 partners from EU, UK, South Africa and is, coordinated by Oulu Mining School (OMS).

Open position

The PhD project includes working on optimizing mineral resource modelling using machine learning approaches. Reference sites include magmatic Ni-Cu-PGE-V-Ti deposits in Finland, Poland and Czech Republic.

Traditional resource modelling approaches include using a set of geostatistical techniques that in the end results estimate of grade distribution within given mineral deposit. Different type of interpolation methods are used (e.g. Kriging) to predict grade in unknown locations based on the adjacent measured known values. There are several possible human based errors during the mineral resource estimation workflow. Machine learning algorithms have developed drastically during the recent decades due to the increase in the computational power. The potential gain for using machine learning in the resource modelling is to reduce the human based errors, increase the automatization of the process, and result more accurate estimations of the grade within the ore domains.  The PhD is supervised by Dr. Jukka-Pekka Ranta (OMS) and Professor John Carranza (University of Free State, South Africa)

Qualification requirements

- M. Sc. degree in the relevant field. Ability to work in international research groups.

- Background on statistics or high motivation to learn to work with large geochemical datasets.

- Background in data science programming languages (e.g. R, python). Experience in mineral resource estimation or 3D modelling is seen as benefit.

We expect a highly motivated candidate with a master´s degree in geosciences, or in related subject. Master´s degree must have been completed by July 2022. The earliest starting date will be 1 August 2022.

We expect excellent spoken and written English skills as this is needed to work in multidisciplinary and international research groups.

What we offer

  • 24-months fully funded doctoral researcher position with 12 months/year salary payment.
  • You will become part of international research group including companies, universities and research organizations from Finland, United Kingdom, Poland, Czech Republic and South Africa.
  • You will receive support not only from your team and supervisor, but also from university´s wide variety of support services, so that you can excel in your studies and research / work.
  • In addition to modern research facilities, we offer you personnel benefits such as occupational healthcare, sports, culture and wellness benefits.
  • Flexible working hours (1612 hours/year)

Other benefits: The successful candidate will receive full benefits provided by the University of Oulu to university employees, including free time corresponding to holidays and free occupational health care services. The successful candidate will receive also benefits provided by the Finnish government to residents, for example possibility to obtain access to the national healthcare system, tax benefits for employees with children and high-quality affordable childcare services.

Salary

For doctoral researcher salary is in accordance with the Finnish universities salary system (for teaching and research personnel): A Doctoral Researcher level 2 – 4. In addition, a salary component based on personal work performance will be paid (maximum of 50% of the job-specific component). Typical starting salary for a Doctoral Researcher is approx. 2400-2700€ per month (before taxes). A trial period of six months will be applied.

How to apply

Applications, together with all relevant enclosures, should be submitted using the electronic application form by 31st of May 2022 at 23:59 (Finnish local time). The application should be written in English and include the following:

1)     A motivation letter (max. 2 pages) summarizing applicant’s professional experience and expertise and describing why applicant is interested in about this position. Also, information on personal research interests, experience and career plans are valuable to provide here

2)     Curriculum vitae (max. 4 pages) in accordance with the guidelines of the Finnish Advisory Board on Research Integrity http://www.tenk.fi/en/template-researchers-curriculum-vitae

3)     List of publications (if applicable) based on the guidelines of the Academy of Finland https://www.aka.fi/en/funding/apply-for-funding/az-index-of-application-guidelines/list-of-publications/

4)     Certificates/Diplomas: Scanned copy of the original master`s degree certificate and transcript of records and, when necessary, official translations to Finnish or English

5)     Contact information of two senior/experienced researchers who may be asked to give a statement on the candidate

Only applications containing all relevant appendices and submitted through e-recruitment system will be considered. Top candidates will be invited to an on-site or remote interview.

Further information

Faculty of Technology, Oulu Mining School

University Lecturer Jukka-Pekka Ranta, jukka-pekka.ranta@oulu.fi

Professor Shenghong Yang, shenhong.yang@oulu.fi


In your application, please refer to Polytechnicpositions.com

FACEBOOK
TWITTER
LINKEDIN

baner1

baner10

baner12

baner14

baner2

baner3

baner4

baner5

baner6

baner7

baner8

baner9