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remote areas in the Himalayas. The company will host the battery demonstrator at its premises in Kathmandu. You will be an applied engineer, battery technologist or materials scientist who holds a PhD
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for researchers early in their careers. Successful candidates are expected to be either graduate students, probably in the latter stages of their research leading to a PhD Degree, or post-doctoral researchers who
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latter stages of their research leading to a PhD Degree, or post-doctoral researchers who have recently been awarded their PhD Degree. Candidates who have undertaken more than five years of full-time
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to gender—and demonstrated expertise in advanced statistical methods (e.g., multilevel modelling). The successful candidate will work closely with the Principal Investigator, Dr. Verena Klein, a PhD student
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-informed machine learning (PIML) models for the prediction of physical and chemical properties using data from experiments and computation constrained by physics requirements. § Implementing algorithms
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will normally be either postdoctoral researchers who have recently submitted their PhD, or graduate students in the latter stages of research leading to a PhD. Candidates should have either: Submitted
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A well-qualified candidate should: (1) be passionate about research; (2) have a PhD degree in Chemical Engineering or Chemistry, or at least, have submitted PhD thesis; (3) be an expert of chemical
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HiPerBreedSim project. In this role, you will leverage recent advances in working with ancestral recombination graphs (ARGs) to develop algorithms and code for simulating population genomic data, including
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include but are not limited to: network architecture design for NTN and terrestrial network (TN) convergence, intelligent traffic steering algorithms between TN and NTN, orchestration of TN/NTN resources
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with enhanced properties. Appointments will initially be made on a 1-year contract, with the possibility of extension. PhD holders with no prior experience in phage-based evolution systems are welcome